How Efficient is Your Data Blending?

Jovan King's picture
Efficient data blending is important for effective analysis.

One of big data's most significant advantages is the insight analysis provides, which can help companies make carefully informed decisions. With data streaming available from numerous sources, businesses face many challenges in gathering, storing and making sense of large volumes of information. I recently read a TechRepublic article that discusses how "data blending" impacts the insights that can be derived from big data. The key to success is preparing the data so it will be easy to use.

Data must be properly prepared before it can be analyzed. Professionals tasked with managing the data must first store it before cleaning and examining its quality. However, if it becomes too difficult to get the data ready for analysis, businesses may lose out on the opportunity to use it. "A person running marketing or sales needs to be empowered to know what they're looking at," Jaime Merritt, vice president of product marketing for Progress Software tells TechRepublic. "Because no matter how many features or algorithms you employ with this data, you will only get your data analysts querying this data if it is easy to use."

The preparation process can be carried out using more than one method, but there are software tools available to simplify working with millions of rows of data. However, without a great deal of support from an IT team, making this happen can be a daunting task.

Companies without enough IT support to prepare data for analysis can turn to software that will do the legwork for them, instead of potentially spending months trying to blend data on their own. To keep up with data management best practices, IT professionals looking to enhance the data blending process may want to consider data preparation tools that will allow them to complete the process in a short time frame.

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