Best Practices For Data Warehouse Success

When one imagines a warehouse, images of a large storage facility containing endless rows and shelves of physical inventory come to mind. A data warehouse has some semblance to this concept in that it gathers, stores, and processes large amounts of data instead of physical inventory. 

Previously, the function of databases was to store information and retrieve it on demand. This configuration was practical until data volumes exponentially multiplied, requiring more efficient solutions to store and process it. The data warehouse concept was developed in the 1980s in response to this need and can process data from multiple internal and external sources. Data analytics software, trends, and patterns provide guidance for intelligent decision-making.

Criteria For Functional Effectiveness

A data warehouse is of little use if it is poorly designed and not able to handle growth. Without following established criteria, inconsistent and incorrect data can be the result. Wrong data types mean longer loading times and data corruption. Slower load times would severely delay report generation and substantially decrease productivity.

For it to function effectively, the data warehouse solutions must have the following criteria

  • Real-time data that is analytics-ready and always available. 
  • The ability to support thousands of simultaneous users.
  • Have the capability to handle all types and sizes of data. 
  • Use automation throughout the system to improve productivity.
  • Be implemented in a hybrid cloud for cost efficiency and remote access.
  • Use multi-source and database aggregation with incremental database updates.
  • Have a detailed transaction logging process. 

Why Data Warehouse Projects Fail

There are also common reasons that data warehouse projects fail. While there are many reasons for this, the most common pitfalls encountered are as follows: 

  • Failure to define the specific objectives the warehouse will meet.

    Many warehouse implementation projects fail because the system did not adequately meet the needs of the business. This occurs as a result of not addressing the goals at the onset of project planning.  

  • Inadequate quantifying expenditures.

    Since the warehouse grows very fast, the cost justification for this must be considered well ahead of time. Doing so simplifies future funding processes as the warehouse grows over time. 

  • Lack of communication at the user level.

    The success of the warehouse ultimately comes down to the users. They should be educated on data warehousing fundamentals, including the benefits and limitations. Doing so will help them manage their expectations. 

  • Overloading the system with massive amounts of data at the onset.

    Data warehouses are ideally implemented using a phased approach. The chances of failure increase dramatically if there is an overload of data from the start. By slowly phasing in the warehouse usage, it can also assist in the learning curve of the project team and end-users. The highest probability for success occurs in building the warehouse using a more gradual process. 

Data Warehouse Security

No discussion on data warehouse best practices would be complete without addressing the security of the system. 

Unauthorized access to an organization’s data warehouse can have devastating effects such as breach of customer data and high-level company information exposure. The following must be taken into consideration when selecting methods for airtight security for the warehouse.

  • How to balance access between less secure data for specific users while maintaining tighter restrictions for analytics and other crucial business intelligence.
  • Classifying users for access by using either a hierarchical or role-based approach.
  • Selecting systems and processes to effectively secure the warehouse. Would encrypting data be enough or are more elaborate security measures needed?
  • How will the security features ultimately affect warehouse performance, such as system slowdowns and reporting delays.

The choice of which security protocol to use ultimately depends on how cost-effective it is in relation to the amount of protection needed. 

At Helios, our team of experts can assist with data warehouse development and maintenance strategies to ensure your company’s success. Contact us for more information on our complete line of data solutions that can take your business to the next level. 



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