Data Architecture

Companies generate tremendous amounts of data, which is often supplemented with even more external data.  Hence, the problem becomes how to effectively use this vast store of data to better manage the business and find otherwise unusual opportunities.

The place to start is Data Architecture.  In its simplest form, the Data Architecture describes a company’s data assets and the governance processes to ensure data integrity.  Specific aspects of data architecture are procedures, practices, rules, standards and models that govern data collection; data arrangement; data integration; data quality; master data management; data storage; data exploration and data visualization.

Being awash in data imposes new demands on IT to organize and manage this asset.  There is a large array of tools to help manage data and make it available to end users.

We are experienced in managing data generated by internal business systems and integrating external data with it.

One example is a multinational corporation for which we designed a Hyperion data warehouse to aggregate the company’s financial data and a web front end to allow corporate and the 2 dozen plus subsidiaries to maintain their data.  This environment enabled the company to consolidate all of its financial information in a single repository, instead of more than 2 dozen separate datastores sprinkled around the world.  This in turned allowed the company to move its financial reporting from a spreadsheet jungle to a single centralized data repository.  (To get an idea of the magnitude of the project think about every data element that appears on financial statements and then multiple that by 26 subsidiaries.)

For another client, we designed several Data Marts and a Data Warehouse to ingest data from multiple external vendors.  The client scrubs, organizes and re-organizes the data and in turn makes it available to its clients.  They consume the data via reports and dashboards including the latest data visualization techniques. 

For other clients, we have built various data bridges to combine and aggregate data in different databases, Data Marts and Data Warehouses for a variety of different purposes.

In the end, IT is all about data … and business process and infrastructure.