Data warehousing

Data warehousing represents the integration, transformation, consolidation, cleanup, and storage of data. It also incorporates the extraction of data for analysis and interpretation. The data warehousing process includes data modeling, data extraction, and administration of the data warehouse management processes.


Business Analytics

Business analytics (BA) refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods.

In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods. Business analytics makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management to drive decision making. Analytics may be used as input for human decisions or may drive fully automated decisions.


Multidimensional database

Multidimensional database (data cubes) as opposed to relational tables enables pre-aggregated data storage by dimension and faster data retrieval when running queries.


OLAP Processor 

OLAP processor (Online Analytical Processing) is a server component. It lies between the end user and the database. It makes the multi-dimensionally formatted data available to front end tools. OLAP processor is optimized for the analysis and reporting of very large datasets.


Data Mining

You can use data mining to automatically determine significant patterns and hidden associations from large amounts of data. Data mining provides you with insights and correlations that had formerly gone unrecognized or been ignored because it had not been considered possible to analyze them.


Agile BI

Agile business intelligence addresses a broad need to enable flexibility by accelerating the time it takes to deliver value with BI projects. It can include technology deployment options such as self-service BI, cloud-based BI, and data discovery dashboards that allow users to begin working with data more rapidly and adjust to changing needs.

To transform traditional BI project development to fit dynamic user requirements, many organizations implement formal methodologies that utilize agile software development techniques and tools to accelerate development, testing, and deployment. Ongoing scoping, rapid iterations that deliver working components, evolving requirements, scrum sessions, frequent and thorough testing, and business/development communication are important facets of a formal agile approach.



Extract, Transform and Load (ETL) is used when implementing certain application logic during data extraction and transformation from source to target.


Big Data Analytics

Big data analytics is the intersection of two technical entities that have come together. First, there’s big data for massive amounts of detailed information. Second, there’s advanced analytics, which can include predictive analytics, data mining, statistics, artificial intelligence, natural language processing, and so on. Put them together and you get big data analytics, the hottest new practice in BI.


Business Analytics with In-memory Databases

The key difference between conventional BI tools and in-memory products is that the former query data on disk while the latter query data in random access memory (RAM). When a user runs a query against a typical data warehouse, the query normally goes to a database that reads the information from multiple tables stored on a server’s hard disk. With a server-based inmemory database, all information is initially loaded into memory. Users then query and interact with the data loaded into the machine’s memory.


Integrated Planning

In SAP BI 7.0 Integrated Planning provides business experts with an infrastructure for realizing and operating planning scenarios. Planning covers a wide range of topics from simple data entry to complex planning scenarios. In contrast to BW-BPS (Business Planning and Simulation), this solution is fully integrated into the BI reporting system.  


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