Data warehouse migration to oracle data integrator 11g

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Pacific Northwest National Laboratory migrated their data warehouse from SQL Server and Visual Basic to Oracle Data Integrator. They developed a SQL parsing tool and used the ODI SDK to programmatically build ODI objects from the SQL metadata, automating the migration of over 4,900 packages. This minimized implementation risks and allowed them to complete the migration in a fraction of the originally estimated 2-3 years. The automated approach reduced human errors and is now used for ongoing operations.

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Data Warehouse Migration to
Oracle Data Integrator 11g
Michael Rainey
Data Warehouse Developer, Business Information Systems
Email: michael.rainey@pnnl.gov
LinkedIn: http://www.linkedin.com/in/rainey
Web: http://www.pnnl.gov

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Pacific Northwest National Laboratory
• Department of Energy research laboratory,
operated by Battelle
– $1.1 billion in business volume in fiscal year 2010
• Mission Outcomes
– Strengthen U.S. scientific foundations for innovation
– Increase U.S. energy capacity and reduce dependence on
imported oil
– Prevent and counter terrorism and proliferation of weapons of
mass destruction
– Reduce environmental effects of human activity and create
sustainable systems

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PNNL Data Warehouse
• Industry standard hub & spoke architecture
• Millions of rows processed daily
– 40+ source applications
– Standardization & transformations performed within the DW
– Final tables replicated to 70+ targets for operational/analytical use
• Legacy software
– Visual Basic 6
– SQL Server 2000 Data Transformation Services (DTS)
Legacy System

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Migration to Oracle Data Integrator
• Minimize implementation risk
– Data warehouse was mature, well designed
– High level of integration within data transformations
• Typical migration of this size estimated to take 2-3 years
– 4900+ DTS packages to migrate
– Interface building & testing estimated based on SQL code
complexity and inexperience with ODI
The Challenge

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Migration to ODI – Conversion Estimate
The Algorithm
Complexity
Level
Point
Analysis
Worst Case -
Hours To
Convert
Best Case -
Hours To
Convert
Transform Gathers and
Distributions
Non-
Standard
Total
Processes
Worst Case -
Est. lbr
hours
Best Case -
Est. lbr
hours
Level 1 1-6 1 0.5 285 4187 0 4472 4472 2236
Level 2 7-11 3 2 137 99 0 236 708 472
Level 3 12-17 5 5 83 32 0 115 575 575
Level 4 18 - 28 10 8 56 16 35 107 1070 856
Level 5 Above 28 15 15 42 7 0 49 735 735
Total 7560 4874
Tight schedule & limited resources led to use of ODI SDK

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Migration to ODI – The Solution
Overview
SQL parse tool
ODI SDK - Java
Build ODI objects

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Migration to ODI – The Solution
Metadata Stored as SQL
SELECT ...
FROM LOCATION_HIERARCHY LH LEFT OUTER JOIN
(
SELECT F.FACILITY_ID, F.FACILITY_ID AS VALUE, ‘ID' AS SOURCE
FROM FACILITY_S1 F
WHERE F.DW_CURRENT_FLAG = 'Y'
UNION
SELECT G.FACILITY_ID, G.ATTRIBUTE_VALUE AS VALUE, 'ALIAS' AS SOURCE
FROM FACILITY_ATTRIBUTE G
WHERE G.ATTRIBUTE_ID = 'BUILDING'
AND G.FACILITY_ID <> G.ATTRIBUTE_VALUE
AND G.DW_CURRENT_FLAG = 'Y'
UNION
SELECT H.FACILITY_ID, H.ATTRIBUTE_VALUE AS VALUE, ‘CORP' AS SOURCE
FROM FACILITY_ATTRIBUTE H
WHERE H.ATTRIBUTE_ID = ‘BUILDINGA'
AND H.FACILITY_ID <> H.ATTRIBUTE_VALUE
AND H.DW_CURRENT_FLAG = 'Y'
UNION
SELECT J.FACILITY_ID, J.LOCATION AS VALUE, ‘MAP' AS SOURCE
FROM LOC_TO_FAC_MAPPING J
WHERE J.DW_CURRENT_FLAG = 'Y'
AND J.FACILITY_ID <> J.LOCATION
) LOCFIS ON LH.LOCATION = LOCFIS.VALUE LEFT OUTER JOIN
( SELECT K.FACILITY_ID, K.FACILITY_ID AS VALUE, ‘ID' AS SOURCE
FROM FACILITY_S1 K
WHERE K.DW_CURRENT_FLAG = 'Y'
UNION
...

8 Copyright © 2011, Oracle and/or its affiliates. All rights
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Migration to ODI – The Solution
Interface Built in ODI

9 Copyright © 2011, Oracle and/or its affiliates. All rights
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Migration to ODI – Success!
• ODI SDK was a key component to a successful migration
• Large volume of ODI objects built in a short period of time
• Risk of human error minimized by automating Interface
creation
• Continued use of ODI SDK for day-to-day operations

10 Copyright © 2011, Oracle and/or its affiliates. All rights
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Thank you!
Michael Rainey
Data Warehouse Developer, Business Information Systems
Email: michael.rainey@pnnl.gov
LinkedIn: http://www.linkedin.com/in/rainey
Web: http://www.pnnl.gov

The chapter discusses the process of migrating to an architected data warehouse environment. It describes developing a migration plan starting with a corporate data model and defining a system of record. The plan also includes designing the data warehouse, building interfaces to load data, and populating the first subject area. An iterative development approach is used where the data architect gets feedback from analysts to continually improve the data warehouse over time. Strategic considerations include addressing both operational and decision support needs.

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I think it’s time for a fresh look at Oracle Data Integrator 12c. What is ODI? How has it evolved over the years and where is it going? And, of course, how do you get started with Oracle Data Integrator? I plan to share what I love about ODI, how to get started building your first ODI project, and what makes Oracle Data Integrator 12c the premier ETL and data warehousing tool on the market. It’s time to get back to the basics! Presented at UTOUG Training Days 2017.

Streaming with Oracle Data IntegrationMichael Rainey

As a data integration professional, it’s almost a guarantee that you’ve heard of real-time stream processing of Big Data. The usual players in the open source world are Apache Kafka, used to move data in real-time, and Spark Streaming, built for in-flight transformations. But what about relational data? Quite often we forget that products incubated in the Apache Foundation can also serve a purpose for “standard” relational databases as well. But how? Well, let’s introduce Oracle GoldenGate and Oracle Data Integrator for Big Data. GoldenGate can extract relational data in real time and produce Kafka messages, ensuring relational data is a part of the enterprise data bus. These messages can then be ingested via ODI through a Spark Streaming process, integrating with additional data sources, such as other relational tables, flat files, etc, as needed. Finally, the output can be sent to multiple locations: on through to a data warehouse for analytical reporting, back to Kafka for additional targets to consume, or any number of targets. Attendees will walk away with a framework on which they can build their data streaming projects, combining relational data with big data and using a common, structured approach via the Oracle Data Integration product stack. Presented at BIWA Summit 2017.

Oracle data integrator 12c - getting startedMichael Rainey

Oracle Data Integrator (ODI) is a data integration tool that can extract, load, and transform heterogeneous data sources. It is flexible and uses a flow-based mapping approach. The presentation provided an overview of ODI and guidance on installation, configuration, and getting started with the developer quickstart to create models, schemas, and mappings between data stores. Key components like knowledge modules generate integration code, while packages and load plans orchestrate the data integration processes.

Oracle GoldenGate and Apache Kafka: A Deep Dive Into Real-Time Data StreamingMichael Rainey

We produce quite a lot of data! Much of the data are business transactions stored in a relational database. More frequently, the data are non-structured, high volume and rapidly changing datasets known in the industry as Big Data. The challenge for data integration professionals is to combine and transform the data into useful information. Not just that, but it must also be done in near real-time and using a target system such as Hadoop. The topic of this session, real-time data streaming, provides a great solution for this challenging task. By integrating GoldenGate, Oracle’s premier data replication technology, and Apache Kafka, the latest open-source streaming and messaging system, we can implement a fast, durable, and scalable solution. Presented at Oracle OpenWorld 2016

Oracle GoldenGate and Apache Kafka A Deep Dive Into Real-Time Data StreamingMichael Rainey

We produce quite a lot of data. Some of this data comes in the form of business transactions and is stored in a relational database. This relational data is often combined with other non-structured, high volume and rapidly changing datasets known in the industry as Big Data. The challenge for us as data integration professionals is to then combine this data and transform it into something useful. Not just that, but we must also do it in near real-time and using a big data target system such as Hadoop. The topic of this session, real-time data streaming, provides us a great solution for that challenging task. By combining GoldenGate, Oracle’s premier data replication technology, and Apache Kafka, the latest open-source streaming and messaging system for big data, we can implement a fast, durable, and scalable solution. This session will walk through the implementation of GoldenGate and Kafka. Presented at Collaborate16 in Las Vegas.

Tame Big Data with Oracle Data IntegrationMichael Rainey

In this session, Oracle Product Management covers how Oracle Data Integrator and Oracle GoldenGate are vital to big data initiatives across the enterprise, providing the movement, translation, and transformation of information and data not only heterogeneously but also in big data environments. Through a metadata-focused approach for cataloging, defining, and reusing big data technologies such as Hive, Hadoop Distributed File System (HDFS), HBase, Sqoop, Pig, Oracle Loader for Hadoop, Oracle SQL Connector for Hadoop Distributed File System, and additional big data projects, Oracle Data Integrator bridges the gap in the ability to unify data across these systems and helps deliver timely and trusted data to analytic and decision support platforms. Co-presented with Alex Kotopoulis at Oracle OpenWorld 2014.

A Picture Can Replace A Thousand WordsMichael Rainey

We all have business user requirements that drive our data warehouse and business intelligence system implementation. Delivered in various formats, these documents, emails, chats, or meeting minutes can be interpreted many different ways, depending on the reader. An effective approach to end the miscommunication...draw a picture. When properly constructed, an architecture diagram, data model, or process model will have only a single meaning. That is why a picture can replace a thousand words. Presented as a TED style talk at Rittman Mead BI Forum 2014.

A Walk Through the Kimball ETL Subsystems with Oracle Data IntegrationMichael Rainey

KScope14 - Real-Time Data Warehouse Upgrade - Success StoriesMichael Rainey

Providing real-time data to its global customers is a necessity for IFPI (International Federation of the Phonographic Industry), a not-for-profit organization with a mission to safeguard the rights of record producers and promote the value of recorded music. Using Oracle Streams and Oracle Warehouse Builder (OWB) for real-time data replication and integration, meeting this goal was becoming a challenge. The solution was difficult to maintain and overall throughput was degrading as data volume increased. The need for greater stability and performance led IFPI to implement Oracle GoldenGate and Oracle Data Integrator. This session will describe the innovative approach taken to complete the migration from a Streams and OWB implementation to a more robust, maintainable, and performant GoldenGate and ODI integrated solution.

Data Warehouse - Incremental Migration to the CloudMichael Rainey

Continuous Data Replication into Cloud Storage with Oracle GoldenGateMichael Rainey

SQL on Hadoop for the Oracle ProfessionalMichael Rainey

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Data warehouse migration to oracle data integrator 11g

1. 1 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Data Warehouse Migration to Oracle Data Integrator 11g Michael Rainey Data Warehouse Developer, Business Information Systems Email: [email protected] LinkedIn: http://www.linkedin.com/in/rainey Web: http://www.pnnl.gov

2. 2 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Pacific Northwest National Laboratory • Department of Energy research laboratory, operated by Battelle – $1.1 billion in business volume in fiscal year 2010 • Mission Outcomes – Strengthen U.S. scientific foundations for innovation – Increase U.S. energy capacity and reduce dependence on imported oil – Prevent and counter terrorism and proliferation of weapons of mass destruction – Reduce environmental effects of human activity and create sustainable systems

3. 3 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 PNNL Data Warehouse • Industry standard hub & spoke architecture • Millions of rows processed daily – 40+ source applications – Standardization & transformations performed within the DW – Final tables replicated to 70+ targets for operational/analytical use • Legacy software – Visual Basic 6 – SQL Server 2000 Data Transformation Services (DTS) Legacy System

4. 4 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Migration to Oracle Data Integrator • Minimize implementation risk – Data warehouse was mature, well designed – High level of integration within data transformations • Typical migration of this size estimated to take 2-3 years – 4900+ DTS packages to migrate – Interface building & testing estimated based on SQL code complexity and inexperience with ODI The Challenge

5. 5 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Migration to ODI – Conversion Estimate The Algorithm Complexity Level Point Analysis Worst Case - Hours To Convert Best Case - Hours To Convert Transform Gathers and Distributions Non- Standard Total Processes Worst Case - Est. lbr hours Best Case - Est. lbr hours Level 1 1-6 1 0.5 285 4187 0 4472 4472 2236 Level 2 7-11 3 2 137 99 0 236 708 472 Level 3 12-17 5 5 83 32 0 115 575 575 Level 4 18 - 28 10 8 56 16 35 107 1070 856 Level 5 Above 28 15 15 42 7 0 49 735 735 Total 7560 4874 Tight schedule & limited resources led to use of ODI SDK

6. 6 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Migration to ODI – The Solution Overview SQL parse tool ODI SDK - Java Build ODI objects

7. 7 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Migration to ODI – The Solution Metadata Stored as SQL SELECT ... FROM LOCATION_HIERARCHY LH LEFT OUTER JOIN ( SELECT F.FACILITY_ID, F.FACILITY_ID AS VALUE, ‘ID' AS SOURCE FROM FACILITY_S1 F WHERE F.DW_CURRENT_FLAG = 'Y' UNION SELECT G.FACILITY_ID, G.ATTRIBUTE_VALUE AS VALUE, 'ALIAS' AS SOURCE FROM FACILITY_ATTRIBUTE G WHERE G.ATTRIBUTE_ID = 'BUILDING' AND G.FACILITY_ID <> G.ATTRIBUTE_VALUE AND G.DW_CURRENT_FLAG = 'Y' UNION SELECT H.FACILITY_ID, H.ATTRIBUTE_VALUE AS VALUE, ‘CORP' AS SOURCE FROM FACILITY_ATTRIBUTE H WHERE H.ATTRIBUTE_ID = ‘BUILDINGA' AND H.FACILITY_ID <> H.ATTRIBUTE_VALUE AND H.DW_CURRENT_FLAG = 'Y' UNION SELECT J.FACILITY_ID, J.LOCATION AS VALUE, ‘MAP' AS SOURCE FROM LOC_TO_FAC_MAPPING J WHERE J.DW_CURRENT_FLAG = 'Y' AND J.FACILITY_ID <> J.LOCATION ) LOCFIS ON LH.LOCATION = LOCFIS.VALUE LEFT OUTER JOIN ( SELECT K.FACILITY_ID, K.FACILITY_ID AS VALUE, ‘ID' AS SOURCE FROM FACILITY_S1 K WHERE K.DW_CURRENT_FLAG = 'Y' UNION ...

9. 9 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Migration to ODI – Success! • ODI SDK was a key component to a successful migration • Large volume of ODI objects built in a short period of time • Risk of human error minimized by automating Interface creation • Continued use of ODI SDK for day-to-day operations

10. 10 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8 Thank you! Michael Rainey Data Warehouse Developer, Business Information Systems Email: [email protected] LinkedIn: http://www.linkedin.com/in/rainey Web: http://www.pnnl.gov

Data warehouse migration to oracle data integrator 11g

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