SSIS control flow
Download as PPTX, PDF5 likes7,050 views
The control flow manages the execution of tasks and containers in an SSIS package. It contains control flow tasks, containers, and precedence constraints. There are three primary control flow objects - tasks that perform jobs, containers that group tasks and containers, and constraints that define execution order. A control flow task performs operations like sending emails or copying files, and completes as succeeded or failed.
1 of 11
Downloaded 293 times
Ad
Recommended
Introduction of ssis
Introduction of ssisdeepakk073 SSIS is a platform for data integration and workflows that allows users to extract, transform, and load data. It can connect to many different data sources and send data to multiple destinations. SSIS provides functionality for handling errors, monitoring data flows, and restarting packages from failure points. It uses a graphical interface that facilitates transforming data without extensive coding.
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI T...
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI T...Edureka! This Edureka SSIS Tutorial will help you learn the basics of MSBI. SSIS is a platform for data integration and workflow applications. This tutorial covers data warehousing concepts which is used for data extraction, transformation and loading (ETL). It is ideal for both beginners and professionals who want to brush up their basics of MSBI. Below are the topics covered in this tutorial:
1. Why do we need data integration?
2. What is data integration?
3. Why SSIS?
4. What is SSIS?
5. ETL process
6. Data Warehousing
7. Installation
8. What is SSIS Package?
SQL Server Integration Services
SQL Server Integration ServicesRobert MacLean The presentation from my talk on what is SQL Server Integration Services (SSIS). It looks at it in Microsoft SQL Server 2008.
Ssis 2008
Ssis 2008maha2886 SQL Server Integration Services (SSIS) is a platform for building extract, transform, and load (ETL) packages and other data integration and workflow tasks. It includes graphical tools and wizards to design packages, as well as utilities to run, debug, and deploy packages. Key components of SSIS include control flow tasks, data flows, variables, logging, and support for transactions and restarting failed packages.
SSIS Presentation
SSIS PresentationBarbaraBederman The document describes an OLTP database created for a construction company to store ongoing and closed project data in third normal form. An ETL process was developed using SSIS to load data from Excel spreadsheets and XML files into the database tables. This ETL package was combined with database backup, shrink, and index rebuild processes into a single job scheduled to run regularly via SQL Server Agent. The document includes diagrams and details of the database structure and various SSIS packages developed for the ETL load processes.
MS SQL SERVER: SSIS and data mining
MS SQL SERVER: SSIS and data miningDataminingTools Inc SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications used for extracting, transforming, and loading (ETL) data. SSIS packages contain control flows and data flows to organize tasks for data migration. SSIS provides tools for loading data, transforming data types, and splitting data into training and testing sets for data mining models. It includes data mining transformations in the control flow and data flow environments to prepare and analyze text data for classification, clustering, and association models.
Sql server-integration-services-ssis-step-by-step-sample-chapters
Sql server-integration-services-ssis-step-by-step-sample-chaptersNadinKa Karimou The document provides an overview and steps for creating a SQL Server Integration Services (SSIS) package to import data from a text file into a SQL Server database. The steps include creating an SSIS project in Business Intelligence Development Studio, defining the flat file and database connections as data sources, dragging a data flow task onto the design surface, and using the flat file source and destination tasks to import the data from the text file into a database table. The document is intended to teach readers how to build and execute a basic SSIS package through a sample import example.
Simplify CDC Pipeline with Spark Streaming SQL and Delta Lake
Simplify CDC Pipeline with Spark Streaming SQL and Delta LakeDatabricks Change Data Capture CDC is a typical use case in Real-Time Data Warehousing. It tracks the data change log -binlog- of a relational database [OLTP], and replay these change log timely to an external storage to do Real-Time OLAP, such as delta/kudu. To implement a robust CDC streaming pipeline, lots of factors should be concerned, such as how to ensure data accuracy , how to process OLTP source schema changed, whether it is easy to build for variety databases with less code.
Adf presentation
Adf presentationKaunas Java User Group "Introduction to the Oracle Application Development Framework (ADF)"
In the presentation will be covered basic architecture of ADF, offered functionality, variety of components, customization features, benefits and lacks. Will be a short demo to have a look and feel how it works. Some shares about real world ADF experience.
SQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise ManageabilityDan English Talking about SQL Server Integration Services (SSIS) overview, deployment, security, and manageability
Apache Iceberg: An Architectural Look Under the Covers
Apache Iceberg: An Architectural Look Under the CoversScyllaDB Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of data. A key capability needed to achieve it is hiding the complexity of underlying data structures and physical data storage from users. The de-facto standard has been the Hive table format addresses some of these problems but falls short at data, user, and application scale. So what is the answer? Apache Iceberg.
Apache Iceberg table format is now in use and contributed to by many leading tech companies like Netflix, Apple, Airbnb, LinkedIn, Dremio, Expedia, and AWS.
Watch Alex Merced, Developer Advocate at Dremio, as he describes the open architecture and performance-oriented capabilities of Apache Iceberg.
You will learn:
• The issues that arise when using the Hive table format at scale, and why we need a new table format
• How a straightforward, elegant change in table format structure has enormous positive effects
• The underlying architecture of an Apache Iceberg table, how a query against an Iceberg table works, and how the table’s underlying structure changes as CRUD operations are done on it
• The resulting benefits of this architectural design
Delta from a Data Engineer's Perspective
Delta from a Data Engineer's PerspectiveDatabricks This document describes the Delta architecture, which unifies batch and streaming data processing. Delta achieves this through a continuous data flow model using structured streaming. It allows data engineers to read consistent data while being written, incrementally read large tables at scale, rollback in case of errors, replay and process historical data along with new data, and handle late arriving data without delays. Delta uses transaction logging, optimistic concurrency, and Spark to scale metadata handling for large tables. This provides a simplified solution to common challenges data engineers face.
Snowflake free trial_lab_guide
Snowflake free trial_lab_guideslidedown1 This document provides instructions for a hands-on lab guide to explore the Snowflake data warehouse platform using a free trial. The lab guide walks through loading and analyzing structured and semi-structured data in Snowflake. It introduces the key Snowflake concepts of databases, tables, warehouses, queries and roles. The lab is presented as a story where an analytics team loads and analyzes bike share rider transaction data and weather data to understand riders and improve services.
Snowflake for Data Engineering
Snowflake for Data EngineeringHarald Erb End-to-end Snowflake Solution Study how to ingest and process data from AWS S3 via Snowpipe and Live data from API's via External Functions
3D: DBT using Databricks and Delta
3D: DBT using Databricks and DeltaDatabricks Data Build Tool (DBT) is an open source technology to set up your data lake using best practices from software engineering. This SQL first technology is a great marriage between Databricks and Delta. This allows you to maintain high quality data and documentation during the entire datalake life-cycle. In this talk I’ll do an introduction into DBT, and show how we can leverage Databricks to do the actual heavy lifting. Next, I’ll present how DBT supports Delta to enable upserting using SQL. Finally, we show how we integrate DBT+Databricks into the Azure cloud. Finally we show how we emit the pipeline metrics to Azure monitor to make sure that you have observability over your pipeline.
Liquibase
LiquibaseSergii Fesenko This document discusses Liquibase, an open source database change management tool. It describes how Liquibase tracks changes to a database schema over time by storing them in changesets within XML changelog files. Each changeset can contain changes like creating/dropping tables, columns, indexes, and more. Changelogs allow splitting changes into multiple files and changesets add metadata like author and preconditions. Liquibase supports rolling back changes and diffing databases to generate changesets. It can be run from the command line or integrated with build tools and applications.
Introduction to Tableau
Introduction to TableauKanika Nagpal This document provides an overview and instructions for using Tableau software for data visualization and analysis. It describes Tableau as a tool for simplifying data into understandable formats via dashboards and worksheets. Steps are outlined for connecting a CSV file on demographic data to Tableau, creating a map visualization showing populations by state in India, and differences between live and extract connections. Basic concepts like dimensions, measures, and different methods for creating visualizations through drag and drop or double clicking are also summarized.
Hive
HiveManas Nayak Hive is a data warehouse infrastructure tool used to process large datasets in Hadoop. It allows users to query data using SQL-like queries. Hive resides on HDFS and uses MapReduce to process queries in parallel. It includes a metastore to store metadata about tables and partitions. When a query is executed, Hive's execution engine compiles it into a MapReduce job which is run on a Hadoop cluster. Hive is better suited for large datasets and queries compared to traditional RDBMS which are optimized for transactions.
Elastic Stack Introduction
Elastic Stack IntroductionVikram Shinde Getting Started with Elastic Stack.
Detailed blog for the same
http://vikshinde.blogspot.co.uk/2017/08/elastic-stack-introduction.html
Big data architectures and the data lake
Big data architectures and the data lakeJames Serra The document provides an overview of big data architectures and the data lake concept. It discusses why organizations are adopting data lakes to handle increasing data volumes and varieties. The key aspects covered include:
- Defining top-down and bottom-up approaches to data management
- Explaining what a data lake is and how Hadoop can function as the data lake
- Describing how a modern data warehouse combines features of a traditional data warehouse and data lake
- Discussing how federated querying allows data to be accessed across multiple sources
- Highlighting benefits of implementing big data solutions in the cloud
- Comparing shared-nothing, massively parallel processing (MPP) architectures to symmetric multi-processing (
Talend Data Integration Tutorial | Talend Tutorial For Beginners | Talend Onl...
Talend Data Integration Tutorial | Talend Tutorial For Beginners | Talend Onl...Edureka! The document provides an overview of Talend Open Studio (TOS), an open source data integration platform. It discusses what Talend is, key TOS features like being open source and providing a unified platform. It also describes installing and using TOS, which includes dragging and dropping components onto a design window. Context variables and metadata are important concepts for reusing configurations across environments in TOS.
SQL window functions for MySQL
SQL window functions for MySQLDag H. Wanvik SQL window functions for MySQL. The talk was given at the pre-FOSDEM '17 MySQL day, Brussels, 2017-01-03.
ETL in the Cloud With Microsoft Azure
ETL in the Cloud With Microsoft AzureMark Kromer Short introduction to different options for ETL & ELT in the Cloud with Microsoft Azure. This is a small accompanying set of slides for my presentations and blogs on this topic
Azure Data Factory
Azure Data FactoryHARIHARAN R Azure Data Factory is a data integration service that allows for data movement and transformation between both on-premises and cloud data stores. It uses datasets to represent data structures, activities to define actions on data with pipelines grouping related activities, and linked services to connect to external resources. Key concepts include datasets representing input/output data, activities performing actions like copy, and pipelines logically grouping activities.
What Is RDD In Spark? | Edureka
What Is RDD In Spark? | EdurekaEdureka! *** Apache Spark and Scala Certification Training: https://www.edureka.co/apache-spark-scala-training ***
This Edureka PPT on "RDD Using Spark" will provide you the detailed and comprehensive knowledge about RDD, which are considered to be the backbone of Apache Spark. You will learn about the various Transformations and Actions that can be performed on RDDs. This PPT will cover the following topics:
Need for RDDs
What are RDDs?
Features of RDDs
Creation of RDDs using Spark
Operations performed on RDDs
RDDs using Spark: Pokemon Use Case
Blog Series: http://bit.ly/2VRogGx
Complete Apache Spark and Scala playlist: http://bit.ly/2In8IXD
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
1\9.SSIS 2008R2_Training - Introduction to SSIS
1\9.SSIS 2008R2_Training - Introduction to SSISPramod Singla It's a SQL server 2008R2 SSIS introduction session.These slides will give you brief introduction of SSIS. You can skip the session if you are already know the basics and history of SSIS.
Designing ETL Pipelines with Structured Streaming and Delta Lake—How to Archi...
Designing ETL Pipelines with Structured Streaming and Delta Lake—How to Archi...Databricks Structured Streaming has proven to be the best platform for building distributed stream processing applications. Its unified SQL/Dataset/DataFrame APIs and Spark’s built-in functions make it easy for developers to express complex computations. Delta Lake, on the other hand, is the best way to store structured data because it is a open-source storage layer that brings ACID transactions to Apache Spark and big data workloads Together, these can make it very easy to build pipelines in many common scenarios. However, expressing the business logic is only part of the larger problem of building end-to-end streaming pipelines that interact with a complex ecosystem of storage systems and workloads. It is important for the developer to truly understand the business problem that needs to be solved. Apache Spark, being a unified analytics engine doing both batch and stream processing, often provides multiples ways to solve the same problem. So understanding the requirements carefully helps you to architect your pipeline that solves your business needs in the most resource efficient manner.
In this talk, I am going examine a number common streaming design patterns in the context of the following questions.
WHAT are you trying to consume? What are you trying to produce? What is the final output that the business wants? What are your throughput and latency requirements?
WHY do you really have those requirements? Would solving the requirements of the individual pipeline actually solve your end-to-end business requirements?
HOW are going to architect the solution? And how much are you willing to pay for it?
Clarity in understanding the ‘what and why’ of any problem can automatically much clarity on the ‘how’ to architect it using Structured Streaming and, in many cases, Delta Lake.
Introduction to Tableau 
Introduction to Tableau Mithileysh Sathiyanarayanan This document provides an overview and introduction to Tableau. It outlines the basic steps for connecting to different data sources, building initial views, and creating dashboards. The document covers prerequisites, an introduction to the Tableau workspace, demo instructions for connecting to sample data files and modifying data connections, and includes lab exercises for readers to practice the concepts. The goal is to help readers understand the basics of visualizing and exploring data using Tableau.
Architecture of integration services
Architecture of integration servicesSlava Kokaev SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications. The SSIS architecture includes packages, tasks, containers, variables, connections and event handlers. Packages contain control flow elements, like tasks and containers, that prepare data. Data flow elements in packages extract, transform and load data. The control flow engine manages task execution while the data flow engine moves data between sources and destinations.
SSIS 2008 R2 data flow
SSIS 2008 R2 data flowSlava Kokaev The document discusses the data flow task in SQL Server Integration Services (SSIS). It encapsulates the data flow engine and performs ETL processes like extract, transform, and load data. Data flow components include sources that extract data, transformations that modify data, and destinations that load data. Paths connect the components and create the data flow pipeline. Sources extract from different data sources. Transformations modify data through row-level and rowset operations. Destinations load data to various targets.
Ad
More Related Content
What's hot (20)
Adf presentation
Adf presentationKaunas Java User Group "Introduction to the Oracle Application Development Framework (ADF)"
In the presentation will be covered basic architecture of ADF, offered functionality, variety of components, customization features, benefits and lacks. Will be a short demo to have a look and feel how it works. Some shares about real world ADF experience.
SQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise ManageabilityDan English Talking about SQL Server Integration Services (SSIS) overview, deployment, security, and manageability
Apache Iceberg: An Architectural Look Under the Covers
Apache Iceberg: An Architectural Look Under the CoversScyllaDB Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of data. A key capability needed to achieve it is hiding the complexity of underlying data structures and physical data storage from users. The de-facto standard has been the Hive table format addresses some of these problems but falls short at data, user, and application scale. So what is the answer? Apache Iceberg.
Apache Iceberg table format is now in use and contributed to by many leading tech companies like Netflix, Apple, Airbnb, LinkedIn, Dremio, Expedia, and AWS.
Watch Alex Merced, Developer Advocate at Dremio, as he describes the open architecture and performance-oriented capabilities of Apache Iceberg.
You will learn:
• The issues that arise when using the Hive table format at scale, and why we need a new table format
• How a straightforward, elegant change in table format structure has enormous positive effects
• The underlying architecture of an Apache Iceberg table, how a query against an Iceberg table works, and how the table’s underlying structure changes as CRUD operations are done on it
• The resulting benefits of this architectural design
Delta from a Data Engineer's Perspective
Delta from a Data Engineer's PerspectiveDatabricks This document describes the Delta architecture, which unifies batch and streaming data processing. Delta achieves this through a continuous data flow model using structured streaming. It allows data engineers to read consistent data while being written, incrementally read large tables at scale, rollback in case of errors, replay and process historical data along with new data, and handle late arriving data without delays. Delta uses transaction logging, optimistic concurrency, and Spark to scale metadata handling for large tables. This provides a simplified solution to common challenges data engineers face.
Snowflake free trial_lab_guide
Snowflake free trial_lab_guideslidedown1 This document provides instructions for a hands-on lab guide to explore the Snowflake data warehouse platform using a free trial. The lab guide walks through loading and analyzing structured and semi-structured data in Snowflake. It introduces the key Snowflake concepts of databases, tables, warehouses, queries and roles. The lab is presented as a story where an analytics team loads and analyzes bike share rider transaction data and weather data to understand riders and improve services.
Snowflake for Data Engineering
Snowflake for Data EngineeringHarald Erb End-to-end Snowflake Solution Study how to ingest and process data from AWS S3 via Snowpipe and Live data from API's via External Functions
3D: DBT using Databricks and Delta
3D: DBT using Databricks and DeltaDatabricks Data Build Tool (DBT) is an open source technology to set up your data lake using best practices from software engineering. This SQL first technology is a great marriage between Databricks and Delta. This allows you to maintain high quality data and documentation during the entire datalake life-cycle. In this talk I’ll do an introduction into DBT, and show how we can leverage Databricks to do the actual heavy lifting. Next, I’ll present how DBT supports Delta to enable upserting using SQL. Finally, we show how we integrate DBT+Databricks into the Azure cloud. Finally we show how we emit the pipeline metrics to Azure monitor to make sure that you have observability over your pipeline.
Liquibase
LiquibaseSergii Fesenko This document discusses Liquibase, an open source database change management tool. It describes how Liquibase tracks changes to a database schema over time by storing them in changesets within XML changelog files. Each changeset can contain changes like creating/dropping tables, columns, indexes, and more. Changelogs allow splitting changes into multiple files and changesets add metadata like author and preconditions. Liquibase supports rolling back changes and diffing databases to generate changesets. It can be run from the command line or integrated with build tools and applications.
Introduction to Tableau
Introduction to TableauKanika Nagpal This document provides an overview and instructions for using Tableau software for data visualization and analysis. It describes Tableau as a tool for simplifying data into understandable formats via dashboards and worksheets. Steps are outlined for connecting a CSV file on demographic data to Tableau, creating a map visualization showing populations by state in India, and differences between live and extract connections. Basic concepts like dimensions, measures, and different methods for creating visualizations through drag and drop or double clicking are also summarized.
Hive
HiveManas Nayak Hive is a data warehouse infrastructure tool used to process large datasets in Hadoop. It allows users to query data using SQL-like queries. Hive resides on HDFS and uses MapReduce to process queries in parallel. It includes a metastore to store metadata about tables and partitions. When a query is executed, Hive's execution engine compiles it into a MapReduce job which is run on a Hadoop cluster. Hive is better suited for large datasets and queries compared to traditional RDBMS which are optimized for transactions.
Elastic Stack Introduction
Elastic Stack IntroductionVikram Shinde Getting Started with Elastic Stack.
Detailed blog for the same
http://vikshinde.blogspot.co.uk/2017/08/elastic-stack-introduction.html
Big data architectures and the data lake
Big data architectures and the data lakeJames Serra The document provides an overview of big data architectures and the data lake concept. It discusses why organizations are adopting data lakes to handle increasing data volumes and varieties. The key aspects covered include:
- Defining top-down and bottom-up approaches to data management
- Explaining what a data lake is and how Hadoop can function as the data lake
- Describing how a modern data warehouse combines features of a traditional data warehouse and data lake
- Discussing how federated querying allows data to be accessed across multiple sources
- Highlighting benefits of implementing big data solutions in the cloud
- Comparing shared-nothing, massively parallel processing (MPP) architectures to symmetric multi-processing (
Talend Data Integration Tutorial | Talend Tutorial For Beginners | Talend Onl...
Talend Data Integration Tutorial | Talend Tutorial For Beginners | Talend Onl...Edureka! The document provides an overview of Talend Open Studio (TOS), an open source data integration platform. It discusses what Talend is, key TOS features like being open source and providing a unified platform. It also describes installing and using TOS, which includes dragging and dropping components onto a design window. Context variables and metadata are important concepts for reusing configurations across environments in TOS.
SQL window functions for MySQL
SQL window functions for MySQLDag H. Wanvik SQL window functions for MySQL. The talk was given at the pre-FOSDEM '17 MySQL day, Brussels, 2017-01-03.
ETL in the Cloud With Microsoft Azure
ETL in the Cloud With Microsoft AzureMark Kromer Short introduction to different options for ETL & ELT in the Cloud with Microsoft Azure. This is a small accompanying set of slides for my presentations and blogs on this topic
Azure Data Factory
Azure Data FactoryHARIHARAN R Azure Data Factory is a data integration service that allows for data movement and transformation between both on-premises and cloud data stores. It uses datasets to represent data structures, activities to define actions on data with pipelines grouping related activities, and linked services to connect to external resources. Key concepts include datasets representing input/output data, activities performing actions like copy, and pipelines logically grouping activities.
What Is RDD In Spark? | Edureka
What Is RDD In Spark? | EdurekaEdureka! *** Apache Spark and Scala Certification Training: https://www.edureka.co/apache-spark-scala-training ***
This Edureka PPT on "RDD Using Spark" will provide you the detailed and comprehensive knowledge about RDD, which are considered to be the backbone of Apache Spark. You will learn about the various Transformations and Actions that can be performed on RDDs. This PPT will cover the following topics:
Need for RDDs
What are RDDs?
Features of RDDs
Creation of RDDs using Spark
Operations performed on RDDs
RDDs using Spark: Pokemon Use Case
Blog Series: http://bit.ly/2VRogGx
Complete Apache Spark and Scala playlist: http://bit.ly/2In8IXD
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
1\9.SSIS 2008R2_Training - Introduction to SSIS
1\9.SSIS 2008R2_Training - Introduction to SSISPramod Singla It's a SQL server 2008R2 SSIS introduction session.These slides will give you brief introduction of SSIS. You can skip the session if you are already know the basics and history of SSIS.
Designing ETL Pipelines with Structured Streaming and Delta Lake—How to Archi...
Designing ETL Pipelines with Structured Streaming and Delta Lake—How to Archi...Databricks Structured Streaming has proven to be the best platform for building distributed stream processing applications. Its unified SQL/Dataset/DataFrame APIs and Spark’s built-in functions make it easy for developers to express complex computations. Delta Lake, on the other hand, is the best way to store structured data because it is a open-source storage layer that brings ACID transactions to Apache Spark and big data workloads Together, these can make it very easy to build pipelines in many common scenarios. However, expressing the business logic is only part of the larger problem of building end-to-end streaming pipelines that interact with a complex ecosystem of storage systems and workloads. It is important for the developer to truly understand the business problem that needs to be solved. Apache Spark, being a unified analytics engine doing both batch and stream processing, often provides multiples ways to solve the same problem. So understanding the requirements carefully helps you to architect your pipeline that solves your business needs in the most resource efficient manner.
In this talk, I am going examine a number common streaming design patterns in the context of the following questions.
WHAT are you trying to consume? What are you trying to produce? What is the final output that the business wants? What are your throughput and latency requirements?
WHY do you really have those requirements? Would solving the requirements of the individual pipeline actually solve your end-to-end business requirements?
HOW are going to architect the solution? And how much are you willing to pay for it?
Clarity in understanding the ‘what and why’ of any problem can automatically much clarity on the ‘how’ to architect it using Structured Streaming and, in many cases, Delta Lake.
Introduction to Tableau
Introduction to Tableau Mithileysh Sathiyanarayanan This document provides an overview and introduction to Tableau. It outlines the basic steps for connecting to different data sources, building initial views, and creating dashboards. The document covers prerequisites, an introduction to the Tableau workspace, demo instructions for connecting to sample data files and modifying data connections, and includes lab exercises for readers to practice the concepts. The goal is to help readers understand the basics of visualizing and exploring data using Tableau.
Viewers also liked (20)
Architecture of integration services
Architecture of integration servicesSlava Kokaev SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications. The SSIS architecture includes packages, tasks, containers, variables, connections and event handlers. Packages contain control flow elements, like tasks and containers, that prepare data. Data flow elements in packages extract, transform and load data. The control flow engine manages task execution while the data flow engine moves data between sources and destinations.
SSIS 2008 R2 data flow
SSIS 2008 R2 data flowSlava Kokaev The document discusses the data flow task in SQL Server Integration Services (SSIS). It encapsulates the data flow engine and performs ETL processes like extract, transform, and load data. Data flow components include sources that extract data, transformations that modify data, and destinations that load data. Paths connect the components and create the data flow pipeline. Sources extract from different data sources. Transformations modify data through row-level and rowset operations. Destinations load data to various targets.
05 SSIS Control Flow
05 SSIS Control FlowSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS) and focuses on defining control flow and data flow objects. It describes the three primary types of control flow objects - tasks, containers, and constraints - and provides examples of common tasks and containers used in SSIS packages to manage workflow and data transformation. It also discusses using variables to store and pass information between different objects in the package control flow.
06 SSIS Data Flow
06 SSIS Data FlowSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS). It describes how SSIS uses a data flow model to extract, transform, and load data. The data flow task encapsulates the data flow engine and connects components together in a pipeline. The key components of the data flow are sources that extract data, transformations that modify data, and destinations that load data. Paths connect the components and define the data flow.
Advanced integration services on microsoft ssis 1
Advanced integration services on microsoft ssis 1Skillwise Group In this presentation skillwise provides you the detailed description about Advanced integration services .
Control Flow Using SSIS
Control Flow Using SSISRam Kedem The document discusses different types of control flow containers in SSIS including precedence constraints, sequence containers, foreach loops, and for loops. Precedence constraints control package flow based on task success, failure or completion. Sequence containers group tasks into separate control flows. Foreach loops repeat a control flow for each item in a collection, while for loops repeat based on a conditional expression.
SSIS Data Flow Tasks 
SSIS Data Flow Tasks Ram Kedem The document provides an overview of various SSIS data flow tasks including connection managers, derived columns, aggregates, lookups, joins, unions, splits, multicasts, conversions and more. It describes what each task does, how it works, and examples of how to use it in an ETL process. The tasks are building blocks that can be combined to construct complex data integration and transformation solutions.
Career Fair 2012-13
Career Fair 2012-13Shaker Schools Mrs. Flynn's class held a career fair on March 1, 2013 where students presented on their potential career choices, which included careers in education, healthcare, athletics, engineering, arts, and more. Students showcased their interests in becoming elementary teachers, veterinarians, navy seals, fitness instructors, bakers, librarians, fashion designers, authors, robotics engineers, and models.
Order by and join
Order by and joinRiteshkiit The document discusses how data is stored and organized in Microsoft SQL Server. It explains that rows in a table will always appear in the order they were inserted by default. It also describes how data is stored across 8KB pages that are grouped into extents for storage management, and how rows cannot span multiple pages. The document also provides an overview of different types of JOINs between tables like INNER, LEFT OUTER, RIGHT OUTER, and FULL OUTER JOINs.
03 Integration Services Project
03 Integration Services ProjectSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS) projects. It states that in SQL Server Business Intelligence Development Studio, an SSIS project is a container that stores and groups the files related to an SSIS package, including the package file, data sources, data source views, and other miscellaneous files. It provides details on how to structure an SSIS project and create packages within a project in Business Intelligence Development Studio.
SQLDay2013_ChrisWebb_CubeDesign&PerformanceTuning
SQLDay2013_ChrisWebb_CubeDesign&PerformanceTuningPolish SQL Server User Group This document provides an overview of a training session on designing and tuning SSAS multidimensional models. The agenda covers topics like dimension design, measure groups, attribute relationships, aggregations, and query performance tuning. It also introduces the speaker and their experience with SQL Server Analysis Services.
Professional Recycling - SSIS Custom Control Flow Components With Visual Stud...
Professional Recycling - SSIS Custom Control Flow Components With Visual Stud...Wolfgang Strasser This document discusses creating custom control flow components for SQL Server Integration Services (SSIS) using Visual Studio Community. It covers the development environment, creating a new custom component project, deploying the component, accessing variables, debugging, internationalization, and best practices like automated builds and versioning. The presenter demonstrates creating a simple component that reads and writes variables, validating properties, and handling events.
Planning by tasks or logical processes - Luciano Luján Antonietti
Planning by tasks or logical processes - Luciano Luján AntoniettiLuciano L. Antonietti Método de planificación que se basa en seguir una secuencia lógica y razonada de las tareas o procesos a planificar. El mismo es una herramienta útil para la elaboración de planes de forma metódica y estandarizada.
9\9 SSIS 2008R2_Training - Package Reliability and Package Execution
9\9 SSIS 2008R2_Training - Package Reliability and Package ExecutionPramod Singla This PPT explains SSIS packages reliability(ACID compliant) and execution options available that exists in SQL Server 2008 R2.
Step by Step design cube using SSAS
Step by Step design cube using SSASAhsan Kabir Say you have made a Data warehouse using dimensional modeling. Now the question will come how you are presenting to your stakeholder. SSRS is a great tools of Microsoft can be used. I am sharing the doc for who is going to start reporting using QUBE. Read this material with source code :
https://gallery.technet.microsoft.com/Step-by-Step-SSRS-Report-8de35ea8
SSIS Basic Data Flow
SSIS Basic Data FlowRam Kedem SQL Server Integration Services (SSIS) is a platform for building data integration and extraction, transformation, and loading (ETL) solutions. It can move data between different data sources simply by copying data over, or in a more complex manner by applying transformations. The document provides an overview of SSIS and demonstrates how to use the SQL Server Import and Export Wizard to perform simple ETL tasks between a SQL database and flat file.
2\9.SSIS 2008R2 _Training - Control Flow
2\9.SSIS 2008R2 _Training - Control FlowPramod Singla This document provides an overview of SQL Server Integration Services (SSIS) including its components, features, and demos. It discusses SSIS packages, control flow and data flow, tasks, containers, precedence constraints, and connection managers. It also mentions importing and exporting data using the Import/Export Wizard or Business Intelligence Development Studio (BIDS). Finally, it lists demo packages for containers and precedence constraints and contact information for questions.
5\9 SSIS 2008R2_Training - DataFlow Basics
5\9 SSIS 2008R2_Training - DataFlow BasicsPramod Singla This document provides an overview of data flow basics in SQL Server Integration Services (SSIS). It discusses the data flow task, pipeline architecture, various data sources including ADO.NET, Excel, flat file, OLE DB, XML, and raw file sources. It also covers data destinations such as OLE DB, DataReader, Excel, flat file, and SQL Server destinations. Finally, it reviews Analysis Services destinations for dimension processing and partition processing and includes demos of various sources and destinations.
Ad
Similar to SSIS control flow (20)
Office 365: Migrating Your Business to Office 365!
Office 365: Migrating Your Business to Office 365!Michael Frank Moving your business to Office 365 may seem like a pretty daunting task but with a careful planning you could be up and running before you know it. In this deep dive we take you through the maze of planning to configuration and mail migration. Exploring simple, staged and hybrid solutions. Packed with tips, tricks and solutions that will ensure your adoption of Office 365 will be a smooth one. We will cover various scenarios, from a simple hosted email migration to the complexities of the Exchange hybrid.
OPEN TEXT ADMINISTRATION
OPEN TEXT ADMINISTRATIONSUMIT KUMAR This document provides an overview of OpenText and its product landscape. It discusses the typical 3-tier architecture with database, application, and presentation layers. It describes the Livelink and Archive Server applications, their architecture, administration tools, and typical document workflows. Key components include the Archive Server, Livelink, Pipeline Server, and various administration tools for managing the OpenText landscape.
24. Advanced Transaction Processing in DBMS
24. Advanced Transaction Processing in DBMSkoolkampus This document discusses various topics related to advanced transaction processing including:
1) Transaction processing monitors provide infrastructure for building transaction processing systems with multiple clients and servers.
2) Main memory databases store data in memory to improve performance by reducing disk access bottlenecks.
3) Workflow systems coordinate the execution of multiple interdependent tasks across different systems while ensuring consistency.
4) Long duration transactions require alternatives to traditional concurrency control and recovery techniques due to their interactive nature.
Sql server lesson9
Sql server lesson9Ala Qunaibi The document discusses how to automate tasks in SQL Server using SQL Server Agent. It describes how SQL Server Agent provides a scheduling engine for automating backups, maintenance tasks, and other processes. It explains how to create jobs composed of steps to execute tasks on a schedule. Job steps can run T-SQL, files, packages and more. Schedules can be defined to control frequency and timing of job execution. Failed jobs and steps are logged to help troubleshoot issues. Alerts can be configured to notify administrators of problems or trigger corrective actions.
MS flow.docx
MS flow.docxSharepoint Designs Microsoft flow is a cloud-based workflow engine, Using Flow end users can create cross application workflows (no code workflows). Flow is a part of office 365 E3 suite. It is a successor of SharePoint designer workflows. Complex level Flows can be promoted to an Azure logic app.
Troubleshooting sql server
Troubleshooting sql serverAntonios Chatzipavlis The document discusses SQL Server monitoring and troubleshooting. It provides an overview of SQL Server monitoring, including why it is important and common monitoring tools. It also describes the SQL Server threading model, including threads, schedulers, states, the waiter list, and runnable queue. Methods for using wait statistics like the DMVs sys.dm_os_waiting_tasks and sys.dm_os_wait_stats are presented. Extended Events are introduced as an alternative to SQL Trace. The importance of establishing a performance baseline is also noted.
Interfaces Demo Eclipsys Baroda India Part Two
Interfaces Demo Eclipsys Baroda India Part TwoMonisha Ghuman The document discusses Eclipsys interfaces and integration components. It describes the hospital integration environment, interface subcomponents like HL7 connections and managers/workers. It explains the inbound and outbound message flows and components of the Sunrise Integration Module and Eclipsys eLink interface engine. Troubleshooting tips are provided along with discussion topics on lab interfaces and the integration of SCM with other systems.
10135 a 11
10135 a 11Bố Su This document provides an overview of monitoring and maintaining Microsoft Exchange Server 2010. It discusses the importance of performance monitoring and tools for monitoring Exchange servers. It also outlines processes for deploying software and hardware updates, developing a troubleshooting methodology, and troubleshooting issues with mailbox servers and client access servers. The document concludes with a lab scenario for hands-on exercises in monitoring Exchange and troubleshooting database availability and client access server issues.
Ssis2008 120710214348-phpapp02
Ssis2008 120710214348-phpapp02sumitkumar3201 SQL Server Integration Services (SSIS) is a platform for building extraction, transformation, and loading (ETL) packages and other data integration tasks. SSIS packages contain graphical tasks and workflows that can be developed using Visual Studio tools and debugged. Packages integrate various data sources, handle data flows between sources and destinations with transformations, and include features for logging, error handling, restarting failed executions, and configuring variables and parameters.
Unit 5 Email FTP Rks.pps.ppt_20240425_112130_0000.pptx
Unit 5 Email FTP Rks.pps.ppt_20240425_112130_0000.pptxAdityaEM08 Institute of Engineering and Technology DCN
Middleware in Asp.Net Core
Middleware in Asp.Net CoreShahriar Hossain Microsoft Silverlight for Windows Phone is a new open-source and cross-platform framework for building modern cloud-based web applications using .NET. It allows for a seamless transition from on-premises to cloud applications and faster development cycles through modular and totally customizable design. The document then provides examples of how to modify request headers, add response headers, validate requests before reaching controllers, and log requests and responses in ASP.NET Core Web API using middleware and delegating handlers.
Splunk for exchange
Splunk for exchangeGreg Hanchin Splunk, Software Tools, Big Data, Logging, PCI, Information security, Cisco Systems, VMware ESX, Regulatory compliance, FISMA, Enterprise architecture, Data center, security software, SCADA, Windows,Unix,Scanners, Citrix, Microsoft Active Directory
Splunk for exchange
Splunk for exchangeGreg Hanchin The Splunk App for Microsoft Exchange provides real-time monitoring and reporting of Microsoft Exchange environments. It collects logs and metrics from Exchange Server and related systems. This allows administrators to view dashboards on server health, message flow, client usage, and capacity planning. Issues can be quickly identified and addressed to maintain high service availability and performance.
Enhancing Your Workflow Automation with Power Automate
Enhancing Your Workflow Automation with Power AutomateBert Blevins Efficiency stands as a paramount concern in today’s swiftly evolving digital landscape. Whether you oversee a large corporation, a small enterprise, or simply your personal tasks, streamlining processes through automation can bolster productivity, reduce errors, and save valuable time. This is where tools like Power Automate step in to offer invaluable assistance.
What is Power Automate?
Microsoft has developed Power Automate, a robust tool tailored for workflow automation needs. This platform, previously known as Microsoft Flow, empowers users to automate tasks across their preferred applications and services, facilitating tasks like file synchronization, notification management, data aggregation, and more, all without requiring extensive coding knowledge.
How Does Power Automate Operate?
At its core, Power Automate operates on a simple principle: when a certain condition is met, an action follows. Users construct workflows, termed “flows,” comprising triggers and actions. Triggers, such as receiving an email or adding a file to a folder, kickstart the flow in response to specific events. Actions denote the tasks executed as a consequence of the trigger, such as sending an email, updating a spreadsheet, or posting a message on a chat platform.
Key Highlights of Power Automate
Power Automate seamlessly integrates with a plethora of Microsoft and third-party apps like Office 365, SharePoint, Dynamics 365, and Salesforce, facilitating automation across diverse platforms and services. The mobile app ensures accessibility from any location, enabling users to create, monitor, and manage workflows directly from their mobile devices. Power Automate offers robust analytics tools for monitoring workflow performance, pre-built templates for common scenarios, and extensive customization options, allowing users to tailor processes to suit their specific requirements.
Three tier Architecture of ASP_Net
Three tier Architecture of ASP_NetBiswadip Goswami This slide show would talk about the 3-tier architecture and how is it helpful and about .NET Platform.
I came up with some Networking Stuffs at http://www.youtube.com/bgccnadom. Try them if you like...
THANK YOU FOR YOUR SUPPORT AND LIKES.
Workflow Management Solutions
Workflow Management SolutionsINFINITE IT Solutions Workflow Business Case: using workflow solution to manage the process of product return. Apart from the case, this presentation will help you understand the nuts & bolts of workflow management systems for enterprise use. For more info about Workflow, visit our website: www.infinite-b2b.ae
FME World Tour 2015 - FME & Data Migration Simon McCabe
FME World Tour 2015 - FME & Data Migration Simon McCabeIMGS Data migration best practice s and procedures with
examples\scenarios from large migrations of utility data
(Water and Electric Data) including:
Designing the migration process
Tools to use in the process
Reporting\Reconciliation processes
Data cleansing
Cutover\Deployment consideration s
Chapter03 Creating And Managing User Accounts
Chapter03 Creating And Managing User AccountsRaja Waseem Akhtar This document provides an overview of managing user accounts in a Microsoft Windows Server 2003 environment. It discusses the purpose of user accounts and the authentication process. It also describes how to create and manage local, roaming, and mandatory user profiles. Various methods for creating and modifying user accounts using tools like Active Directory Users and Computers and command line utilities are presented.
Etl process in data warehouse
Etl process in data warehouseKomal Choudhary The ETL process in data warehousing involves extraction, transformation, and loading of data. Data is extracted from operational databases, transformed to match the data warehouse schema, and loaded into the data warehouse database. As source data and business needs change, the ETL process must also evolve to maintain the data warehouse's value as a business decision making tool. The ETL process consists of extracting data from sources, transforming it to resolve conflicts and quality issues, and loading it into the target data warehouse structures.
Many Faces Of Bi Publisher In Oracle Ebs
Many Faces Of Bi Publisher In Oracle EbsHossam El-Faxe The document discusses the standard and non-standard implementations of Oracle's BI Publisher tool within Oracle EBS applications. It provides an overview of the standard data model, layout templates, report creation, and delivery methods. Examples are also given of variations seen in applications like Advanced Collections, Advanced Procurement, and Payables.
Ad
More from Slava Kokaev (14)
Introduction to Azure Stream Analytics
Introduction to Azure Stream AnalyticsSlava Kokaev This document provides an introduction and overview of Azure Stream Analytics presented by Slava Kokaev. The summary includes:
- Slava Kokaev introduces Azure Stream Analytics and discusses its key capabilities including ease of use, low cost, reliability, connectivity, ability to join streams with reference data, and scalability.
- The architecture of Azure Stream Analytics is explained, including how it connects to data sources like Event Hubs and outputs data to services like Power BI. Stream analytics jobs have inputs, queries to transform data, and outputs.
- The presentation covers the Stream Analytics query language and temporal windows like tumbling, hopping, and sliding windows that can be used to analyze streaming data.
Introduction to Azure Data Factory
Introduction to Azure Data FactorySlava Kokaev Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data. In this session we will learn how to create data integration solutions using the Data Factory service and ingest data from various data stores, transform/process the data, and publish the result data to the data stores.
Business process modeling and analysis for data warehouse design
Business process modeling and analysis for data warehouse designSlava Kokaev The document discusses business process modeling and analysis for data warehouse design. It provides an overview of key concepts like business intelligence, business processes, dimensional modeling and ETL. The document presents examples of modeling dimensions, hierarchies and fact tables to design a dimensional schema for a reseller sales scenario. It also shows examples of identifying business processes and mapping them to the dimensional model for analysis in a data warehouse.
Introduction BI Semantic Model with Sql Server Data Tools copy
Introduction BI Semantic Model with Sql Server Data Tools copySlava Kokaev This document provides an introduction to Business Intelligence Semantic Model (BISM) architecture. It discusses BISM as a single model for various end user experiences, including PowerPivot for Excel, PowerPivot for SharePoint, and organizational BI. It also outlines the BISM architecture, including data access and storage options like VertiPaq, MOLAP, and DirectQuery. Finally, it briefly discusses tools for tabular model development like SQL Server Data Tools and the tabular model development process.
Architecture modeling with UML and Visual Studio 2010 Ultimate
Architecture modeling with UML and Visual Studio 2010 UltimateSlava Kokaev The document discusses UML (Unified Modeling Language) diagrams that can be created in Visual Studio 2010. It provides brief definitions and descriptions of common UML diagram types including class diagrams, package diagrams, activity diagrams, component diagrams, use case diagrams, sequence diagrams, and layer diagrams. It then provides examples of how these diagrams can be used to model business processes, functional systems, and a sales business case.
SSIS Connection managers and data sources
SSIS Connection managers and data sourcesSlava Kokaev This document discusses SSIS data sources and connections. It provides an overview of different types of connections that can be used in SSIS packages, including OLEDB, ADO.NET, flat file, FTP, and Excel connections. Examples are given for Oracle and SQL Server OLEDB connection strings. The resources section links to Microsoft documentation on SSIS connections and data sources for further reference.
Data visualization
Data visualizationSlava Kokaev This document describes three different approaches to building custom business intelligence applications and dashboards:
1) A basic BI approach using ASP.NET, SQL Server 2008 R2, Excel 2007 and report server for static reporting and simple pivot analysis.
2) An approach using PowerPivot for SharePoint 2010, which enables advanced slicing and dicing of data in Excel 2010 and self-service reporting and interactive dashboards in Internet Explorer 8.
3) A more advanced custom BI portal approach using ASP.NET, SQL Server 2008 R2, and Data Dynamics BI Suite for interactive reporting, dashboards and personalized analytics accessed through Excel, PowerPivot and Internet Explorer 8.
Developing ssas cube
Developing ssas cubeSlava Kokaev This document discusses designing and developing OLAP cubes and multidimensional structures. It provides an introduction to OLAP and covers components of cubes like dimensions, measures, and data sources. It also outlines the steps to build a cube in SSAS including creating the data source view, dimensions, measures, and deploying the database. Calculations, KPIs, perspectives and other advanced features are also briefly mentioned.
Business intelligence architecture
Business intelligence architectureSlava Kokaev This document provides an overview of business intelligence and outlines a conceptual framework for designing a business intelligence system driven by business processes. It discusses understanding the business system, defining business processes and requirements, technical design including databases and ETL, and developing BI applications to optimize operations, analyze and control business processes, and monitor business performance. An example sales process is described to illustrate how the framework can be applied.
Designing and developing Business Process dimensional Model or Data Warehouse
Designing and developing Business Process dimensional Model or Data WarehouseSlava Kokaev This document discusses best practices for designing a dimensional data warehouse model including using a star schema with fact and dimension tables, surrogate keys, snowflaking, slowly changing dimensions, and maintaining historical context when loading new or changed data into dimension tables. It describes the three types of slowly changing dimensions including overwriting existing records, inserting new versioned records, and tracking limited history with attributes.
SSAS R2 and SharePoint 2010 – Business Intelligence
SSAS R2 and SharePoint 2010 – Business IntelligenceSlava Kokaev This document discusses Microsoft SQL Server Analysis Services 2008 and enterprise data warehousing. It focuses on analysis services, SQL Server, data mining, and integration services as key components of Microsoft's business intelligence platform for performing analysis on enterprise data warehouses. The platform is designed to provide business insights for improved decision making.
MS SQL Server Analysis Services 2008 and Enterprise Data Warehousing
MS SQL Server Analysis Services 2008 and Enterprise Data WarehousingSlava Kokaev This document discusses business intelligence integration services including SQL Server, data mining, and Analysis Services. It provides an overview of key concepts for building an OLAP cube in Analysis Services such as data sources, data source views, dimensions, hierarchies, and processing cubes. The document also mentions additional cube objects like calculations, KPIs, actions, and perspectives.
01 Architecture Of Integration Services
01 Architecture Of Integration ServicesSlava Kokaev The document discusses the architecture of Microsoft SQL Server Integration Services (SSIS). SSIS is a platform for building data integration and transformation solutions. It allows users to process data into data warehouses, migrate data between systems, integrate data from multiple sources, and cleanse and analyze data. The core components of the SSIS architecture include packages, tasks, containers, control and data flow, connections, variables and event handlers.
Bi Architecture And Conceptual Framework
Bi Architecture And Conceptual FrameworkSlava Kokaev This document discusses business intelligence architecture and concepts. It covers topics like analysis services, SQL Server, data mining, integration services, and enterprise BI strategy and vision. It provides overviews of Microsoft's BI platform, conceptual frameworks, dimensional modeling, ETL processes, and data visualization systems. The goal is to improve organizational processes by providing critical business information to employees.
Recently uploaded (20)
Heap, Types of Heap, Insertion and Deletion
Heap, Types of Heap, Insertion and DeletionJaydeep Kale This pdf will explain what is heap, its type, insertion and deletion in heap and Heap sort
Build Your Own Copilot & Agents For Devs
Build Your Own Copilot & Agents For DevsBrian McKeiver May 2nd, 2025 talk at StirTrek 2025 Conference.
DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptx
DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptxJustin Reock Building 10x Organizations with Modern Productivity Metrics
10x developers may be a myth, but 10x organizations are very real, as proven by the influential study performed in the 1980s, ‘The Coding War Games.’
Right now, here in early 2025, we seem to be experiencing YAPP (Yet Another Productivity Philosophy), and that philosophy is converging on developer experience. It seems that with every new method we invent for the delivery of products, whether physical or virtual, we reinvent productivity philosophies to go alongside them.
But which of these approaches actually work? DORA? SPACE? DevEx? What should we invest in and create urgency behind today, so that we don’t find ourselves having the same discussion again in a decade?
Complete Guide to Advanced Logistics Management Software in Riyadh.pdf
Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company Explore the benefits and features of advanced logistics management software for businesses in Riyadh. This guide delves into the latest technologies, from real-time tracking and route optimization to warehouse management and inventory control, helping businesses streamline their logistics operations and reduce costs. Learn how implementing the right software solution can enhance efficiency, improve customer satisfaction, and provide a competitive edge in the growing logistics sector of Riyadh.
Noah Loul Shares 5 Steps to Implement AI Agents for Maximum Business Efficien...
Noah Loul Shares 5 Steps to Implement AI Agents for Maximum Business Efficien...Noah Loul Artificial intelligence is changing how businesses operate. Companies are using AI agents to automate tasks, reduce time spent on repetitive work, and focus more on high-value activities. Noah Loul, an AI strategist and entrepreneur, has helped dozens of companies streamline their operations using smart automation. He believes AI agents aren't just tools—they're workers that take on repeatable tasks so your human team can focus on what matters. If you want to reduce time waste and increase output, AI agents are the next move.
Andrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell With expertise in data architecture, performance tracking, and revenue forecasting, Andrew Marnell plays a vital role in aligning business strategies with data insights. Andrew Marnell’s ability to lead cross-functional teams ensures businesses achieve sustainable growth and operational excellence.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptx
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55 We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Splunk Security Update | Public Sector Summit Germany 2025
Splunk Security Update | Public Sector Summit Germany 2025Splunk Splunk Security Update
Sprecher: Marcel Tanuatmadja
tecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdffjgm517 descaripcion detallada del avance de las tecnologias en mesopotamia, egipto, roma y grecia.
Cybersecurity Identity and Access Solutions using Azure AD
Cybersecurity Identity and Access Solutions using Azure ADVICTOR MAESTRE RAMIREZ Cybersecurity Identity and Access Solutions using Azure AD
Rusty Waters: Elevating Lakehouses Beyond Spark
Rusty Waters: Elevating Lakehouses Beyond Sparkcarlyakerly1 Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍
Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
HCL Nomad Web – Best Practices and Managing Multiuser Environments
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
Quantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Manifest Pre-Seed Update | A Humanoid OEM Deeptech In France
Manifest Pre-Seed Update | A Humanoid OEM Deeptech In Francechb3 The latest updates on Manifest's pre-seed stage progress.
Into The Box Conference Keynote Day 1 (ITB2025)
Into The Box Conference Keynote Day 1 (ITB2025)Ortus Solutions, Corp This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
SSIS control flow
- 1. The control flow is the workflow engine that contains control flow tasks, containers, and precedence constraints, which manage when tasks and containers execute. The data flow, in contrast, is directly related to processing and transforming data from sources to destinations.
- 2. There are three primary types of control flow objects: Control flow tasks Workflow objects that perform operational- level jobs Control flow containers Provide a grouping mechanism for tasks and other containers Constraints Let you connect tasks and containers and define execution ordering and precedence
- 3. A control flow task is an SSIS component that performs a high level of operations such as sending an e-mail message, executing a SQL statement, or copying a file from an FTP server. When a control flow task is complete, it either succeeded or failed.
- 8. STEP 1 STEP 2 STEP 3 3. Notify Management if @ > 2 2. Send Email to each Customer 1. Retrieve Customers from DB Complete Control Flow
- 9. Full Name Email User::Full Name User::Email User::Customer Records User::Email Counter Email Counter > 2 User::Email Counter COMPLETE COMPLETE STEP 1 STEP 2 STEP 3
- 10. Control Flow Elements- http://msdn.microsoft.com/en-us/library/ms137681.aspx Designing Package Control Flow- http://msdn.microsoft.com/en- us/library/ms140234.aspx
Editor's Notes
- #4: To create a new control flow task in your package, drag the task from the toolbox to theControl Flow tab in the SSIS Designer.After you add a task to the control flow workspace, you need to configure the task to performthe specific operation you selected. To allow configuration, every task has an editor thatyou can open by double-clicking the task or by right-clicking the task and then clicking Edit.Table 1-1 lists the tasks in SSIS under the Control Flow Items list in the toolbox.You might have noticed that there is also a list of Maintenance Plan Tasks for the controlflow. These are primarily for database administrators (DBAs) who are managing SQL Server2008 databases through the SSMS maintenance plan interface or DBAs who are creatingpackages in BIDS for database maintenance.As you can see, SSIS features the ability to perform a host of different processing andintegration operations.
- #6: Variables within SSIS are a way to integrate objects by passing values between tasks and containers, accepting values from external sources, or building code dynamically that is then executed. You can also use variables for auditing and logging.