Business intelligence techniques U2.pptx
- 1. Business intelligence techniques UNIT 2: Business intelligence techniques, data warehousing, data mining and techniques, OLAP, business intelligence system & software.
- 3. Business intelligence analyst • The worldwide economy has taken a significant knock in recent months, and businesses that have managed to endure are now searching for methods to use technological breakthroughs to advance. • A business intelligence strategy is a roadmap that aims to assist businesses in measuring their performance and improving it through architecture and solutions. • Business intelligence analyst abilities are at the forefront of BI plans, especially planning.
- 4. Basic Understanding of BI • Business intelligence (BI) software collects business data and transforms it into practical insights that allow businesses to make educated business judgments. • BI tools allow businesses to access and analyze data through reports, graphs, dashboards, charts, summaries, and maps to develop a BI strategy. • A business intelligence strategy builds a roadmap for applying data in any organization. • PLAN- As by simply adopting the appropriate technology and building a software platform won’t guarantee a profit.
- 5. Basic Understanding of BI To develop a plan, we need clarity of the following 3 things; 1.How will you use the software platform? 2.What data will you manage for analysis? 3.And how will you enable your staff to make informed, data-driven decisions?
- 6. • A business intelligence strategy can help a firm profit from actionable insights. • Eg Access to sales performance benchmarks, human resources salary projections, and ensuring your shipping department understands what to ship each day • A planned approach that includes discovery, planning, and measured execution leads to success. • Business intelligence strategies may help think through all the elements of putting up business intelligence technology and executing everything( from planning to objectives to personnel to ensuring that the new solution is a success). • (BIS)It answers each area of how a firm utilizes data and each step in implementing a business intelligence tool.
- 7. Business intelligence techniques • Business Intelligence is concerned with assisting in decision-making. • BI tools are frequently referred to as Decision Support Systems (DSS) or fact- based support systems because they provide business users with the technology to analyze their data and extract knowledge.
- 8. Business intelligence techniques • Business Intelligence tools usually access the data in a data warehouse. • A data warehouse already contains data from numerous production systems within the organization, • It is cleansed, consolidated, conformed, and stored in one location. • BI applications may focus on analyzing the information (various business intelligence techniques).
- 9. Data visualization • Data is stored as a set or matrix of figures, it is accurate but tough to understand. • For eg Are sales increasing, decreasing, or staying the same? • Analyzing several dimensions of information at once becomes much more difficult. • As a result, data visualization in charts is an easy approach to grasping how to interpret the data immediately.
- 10. Data Mining • Data mining is examining huge amounts of data to detect relevant patterns and rules using automated or semi-automatic means. • a corporate data warehouse possesses an enormous quantity. • Discovering facts that may influence business decisions is very important. • Database researchers employ data mining approaches to reveal hidden patterns and relationships in the data. • Knowledge discovery in databases comprises all of the steps involved in transforming raw data into useful information with any necessary selections, transformations, sub-sampling, and selection of the proper way for transformation.
- 11. Multi-Cloud • Following the outbreak of the pandemic and the national lockdown that ensued, many businesses worldwide began utilizing cloud technologies in their operations. • The advent of cloud technology has had a significant effect on many organizations. Even after the limitations are lifted, companies still prefer to work over the internet because of its ease of use and accessibility. • Thanks to its low cost and easy-to-use features, even R&D projects are being transferred to the cloud.
- 12. Reporting • BI technologies help business users design, schedule, and generate performance, sales, reconciliation, and savings reports. • BI technology-generated reports efficiently gather and present information to aid management, planning, and decision-making. • Once the report is built, it may automatically be sent to a specified distribution list in the proper format with current/weekly/monthly data.
- 13. Time-series Analysis Including (Predictive Techniques) • Every data warehouse and business data is time-based. Product sales, calls, hospitalizations, and so on are just a few examples of this. • It’s critical to show how users’ behavior has evolved regarding product relationships or sales contract modifications due to marketing campaigns. • Future trends or outcomes may be forecast based on previous data.
- 14. Online Analytical Processing (OLAP) • OLAP (Online Analytical Processing) is a fundamental business intelligence approach that solves analytical issues with multiple dimensions. • The multi-dimensional nature of OLAP allows users to examine data concerns from various perspectives, which provides flexibility in dealing with problems. • They can find latent problems by looking at things from different angles. Budgeting, CRM data analysis, and financial prediction are examples of tasks that can be done using OLAP
- 15. Extraction-Transaction-Loading (ETL) • Extraction-Transaction-Loading (ETL) is a specialized business intelligence approach that orchestrates data processing. • It extracts data from storage and converts it to the processor before loading it into the business intelligence system. • They’re commonly used as a transaction tool, which transforms data from numerous sources into data warehouses. • The data is then filtered and moderated by ETL to meet the demands of the business. • It improves the quality level by loading it into end targets such as databases or data warehouses, called quality verification.
- 16. Statistical Analysis • Data analysis begins with the mathematical underpinnings used to assess the significance and trustworthiness of observed connections. • Distribution analysis and confidence intervals (for example, changes in user behaviors, etc.) are impressive features. • The technique of using statistics to establish and evaluate outcomes from data mining is known as statistical analysis.
- 17. Given the enormous amount of Business Intelligence software solutions available, narrowing down the right one for your business can be a tedious process. How does a business start implementing this software? One way to start is by looking at systems that are popular among peers, because those products are the ones that are most likely to stay constantly maintained and upgraded.