Hi-Tech Gateway ::: Data Warehousing

Your company's data is one of its most valuable assets. Critical decisions about your company's future, strategy, and success are made based on the data stored in your information systems. Make your information work for you and enhance decision-making, improve customer service, and increase customer retention.

Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form...

High-performance data warehousing solutions from Hi-Tech Gateway enable global organizations to transform vast information assets into meaningful business intelligence. With a Hi-Tech data warehousing solution, the enterprise can more fully leverage operational data from multiple sources to optimize high-value business processes such as customer interaction strategies, database marketing, supply chain integration, and knowledge management.

Hi-Tech understands the critical nature of your data. That is why our approach keeps the focus on the crucial factors that will impact your data warehouse and data mart projects.

A proven data warehousing methodology based on years of experience is our foundation for implementing solutions for Fortune 1000 clients nationwide. This approach spans the data warehousing lifecycle, which includes:

Data acquisition processes - Extract, transform, load (ETL) This phase includes sourcing, cleansing, transforming, and aggregating data using parallel technology tools to build industrial-strength ETL processes that accommodate high data volumes from disparate sources. Through the cleansing process, we enhance data quality by ensuring data accuracy, type, and consistency, as well as eliminating duplicate records.
Data repositories We are experienced in building a variety of data repositories, including operational data stores, data marts, data warehouses, web warehouses, and data hubs. We start by implementing and properly documenting a physical data model, ensuring data from all functional areas is sufficiently integrated to support cross-functional analyses. We perform database tuning, model denormalization, and aggregation as necessary to support information delivery requirements. When scalability requirements call for it, we partition and distribute data into a parallel architecture.
Cross-channel data integration Data integration across input channels and business units is a top priority for many enterprises. Knightsbridge builds solutions that integrate web and legacy data infrastructures. Real-time solutions help clients obtain an enterprise view of business activity by integrating data from a variety of channels into one high-performance enterprise data warehouse.
Information delivery applications Knightsbridge also specializes in helping clients implement information delivery applications that allow corporate users to access the data in the warehouse. These include decision support tools, data mining and analytic tools, and applications that optimize supply chain, store layouts, campaign management, billing, and industry-specific processes.

We ensure near- and long-term reporting and access requirements are met as well. These may include fixed-frequency static reports; ad-hoc reports; dynamic, multidimensional queries; Internet/intranet application interfaces; and data mining.

As the data warehouse grows, administration (or management) of the repository is a crucial step in optimizing results and return on investment. We provide data warehouse administration services such as performance analysis, user analysis, benchmarking, auditing, and tuning to help clients measure the ongoing success of their data strategies.

Our solutions typically utilize parallel and scalable technologies to implement durable, robust data solutions that can support dramatic increases in data volume and complexity, as well as increased user demand for flexible and timely access to information. If you manage terabyte-class data volumes, integrate e-business and legacy data sources, feed click stream data to analytic or forecasting systems, or find your technology trailing user demands for data access, it's time to look at the cutting edge in high-performance data management.