Ideation’s capabilities include years of experience with OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems leading to high-quality business intelligence solutions. Our experience with traditional database design and development for transaction-based systems complements our dimensional database design and development experience leading to robust reporting solutions. We understand the differences with each approach yet appreciate how the output of one solution (OLTP) serves as the input for the other (OLAP). We also understand the need to customize the ETL (Extraction, Transformation, and Load) processes according to the needs of the customer to comply with organizational standards (e.g., enterprise architecture) and address any technical challenges that may exist (e.g., integration of heterogeneous data sources).

Data Warehousing

Data warehouses encompass a variety of features that assist organizations with increasing efficiency and decision-making capabilities. These features include ad hoc queries, on-demand reports, scheduled reports, dashboards, and scorecards to name a few. The data warehouse serves as a central location for all data needs eliminating the challenge of accessing disparate source systems that may or may not have canned reports meeting the reporting requirements of the organization. In cases where canned reports are available, they are typically a fixed format and rarely capable of being modified. Reporting tools, such as Business Objects, MicroStrategy, and Cognos, provide user-friendly interfaces for developing and modifying reports. Ideation’s experience with data warehousing includes formulating requirements, integrating data sources into an Operational Data Store (ODS), designing/developing star schemas and reports, conducting system integration testing, deployment, and training with Business Objects XI and Structured Query Language (SQL) queries.

Analytics

Analytics covers a broad spectrum of topics but the primary driving force behind analytics is the ability to determine what happened, why it happened, and project what could happen in the future based on historical data. Analytics also involves assessing data quality to determine the root cause of issues and identifying mitigation measures to prevent them from resurfacing. Collecting, integrating, and analyzing data using various methods ensures maximum value is gained from a data warehouse; otherwise, the data warehouse simply becomes a repository of meaningless data. Ideation has experience helping clients with the following types of analysis to transform raw data into actionable information:

• Data Mining to identify trends and extract patterns from the data
• Data Profiling to gather characteristics about the data
• Time-Trending Analysis to perform time-based analysis
• Exception Analysis to identify values that are deemed unacceptable
• Regression Analysis to extrapolate relationships between data elements
• Cluster Analysis to identify taxonomies within the data
• Predictive Analysis to forecast scenarios based on historical data

Ideation also provides training on data analysis techniques that are customized to the client’s data and business processes. We understand the importance of educating users with familiar data to reinforce classroom training.