Teknion's BI consultants solve complex data challenges in dimensional modeling, data integration (ETL), and data quality so that the lack of information is no longer a bottleneck to business growth.
Dimensional Modeling
Dimensional modeling organizes data in structures that are optimal for data warehouses, presenting the data in a framework that is intuitive and allows for high performance access.
Teknion's approach to dimensional modeling starts with an understanding of the business requirements. Our BI consultants align these business requirements with the realities of source data to produce dimensional models that support deep analytics and reporting.
Physical Design
The physical design of a data warehouse establishes the standards and structures that turn the logical design of the dimensional model into the physical database of a data warehouse.
Teknion's BI consultants have expertise in developing the standards and framework that govern the implementation of a physical design. This includes establishing naming conventions, aggregation strategies, indexing and partitioning rules and enterprise security standards.
The combination of the logical dimensional model and the physical design standards results in a physical implementation of tables, views and indexes which support the business requirements for reporting and analytics.
Data Integration (ETL)
The process of integrating data from operational systems is one of the central challenges of building a data warehouse. Poor data quality, diverse source systems, and undocumented business logic are some of the challenges that Teknion's BI consultants are experienced at overcoming.
Our BI consultants begin by analyzing source data using a variety of profiling tools and techniques. This leads to an understanding of the idiosyncrasies of both the business logic and the underlying data. ETL rules are developed in light of these idiosyncrasies to handle standard transformations while also anticipating the exceptions. This approach minimizes the issues which are not typically uncovered until the QA phase.
Getting the data right validates the dimensional model and physical design and is the most critical (and often overlooked) element of an effective data warehouse.
Data Quality
For data to be useful and provide actionable insight to business users it must be clean and consistent. The process of cleansing data from legacy systems is one of the most time consuming and challenging tasks of a BI implementation.
Teknion's BI consultants build data cleansing and quality rules right into the ETL logic. This focus on data quality enables business users to analyze their data consistently and accurately without having to worry about the idiosyncrasies in the source data.