Identifying The Top 3 Data Integration Mistakes, and How to Avoid Them

September 30, 2016 By Trujay Group


    Quite often, the process of data integration is far from seamless resulting in integration mistakes that produce sub-optimal and costly results. To take advantage of the collected data, identifying the top 3 data integration mistakes and avoiding them is critical to the overall business prospects of a company.

    The three most common data integration mistakes are:

  1.  Selecting a data integration solution that scales poorly
  2.  Failing to consider the data types
  3.  Neglecting to provide adequate security

    Frequently, a company selects the data integration option providing the solution needed at the present without considering the future consequences. A non-enterprise level solution might be acceptable for a small company but the performance will rapidly erode as the business grows and more data is ingested from many source systems. Ignoring the latency factor in a data integration solution results in slow performance and unpredictable results that are very difficult to correct.

    Many major data integration mistakes are a result of not understanding the types of data that exist on the various source systems. The presence of proprietary data or data that exists in different storage types such as block storage and data objects produce often produce data integration errors, data mismatches and erroneous data translations among other errors. It is critical for a company to determine the data structures and translations required for data before it reaches the data integration engine.

     Another common integration mistake is failing to consider adequate security protocols when considering a data integration solution. An absence of encryption, identify verification and management and other security features renders the data vulnerable during transmission and storage. Inadequately protected data could result in compliance issues and lawsuits from aggrieved parties when the collected data is compromised.

    Avoiding these top 3 data integration mistakes will permit a company to make advantageous use of their integrated data resulting in increased business and sales growth.

    Interested in learning more? 

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