5 Steps to Data Warehousing Success

Words "data" and "big data" are buzzwords everywhere nowadays. Big data can be used in several different ways to install positive changes and results in your organization. Data warehousing, the digital storage of large amounts of data by companies, can be a huge tool to help increase RoI or indeed a huge drain, with duplicated data being a key problem. Here are five quick tips to map your warehousing journey.


What actually is big data? It is a large amount of data or datasets that have the potential to be mined for value-added insights into either your own operations or processes for operational efficiency and to become more customer-centrically aligned. When used practically and intelligently, Big Data has the potential to create great impacts within a company and thus create Big RoI.

Data warehousing is the digital storage of large amounts of data by companies. This information can be used to analyze a particular subject area by integrating multiple data sources or sets. Historical data is stored in these warehouses and this data is non-volatile and should not be changed. In order to be effective, this warehoused data must be stored in a way that is secure and easy to retrieve and manage.

The main purpose is to track that historical data and analyze the changes over time. This aids in strategic decision-making for businesses. The data is centralized in the warehouse, it is designed to easily link tables from different systems, and it is also designed to ease query writing and optimize reporting speed.

5 Data Warehousing Tips

  1. Identify your existing bottlenecks that are slowing down the flow of information. Performance optimization won’t matter if that is not done first.
  2. The design should always focus on ease of use and speed. Design is very important because users can be distracted by making their data warehouse into an intricate design that sacrifices speed. Speed should always be the number one priority.
  3. Pay close attention to the quality of the data. It needs to be clean and accurate. If not, the output is likely to show discrepancies.
  4. Know your database engine. Knowing the ins and outs of your system is extremely vital for efficiency.
  5. Build for the short-term, but strategize and plan for the future.