Dealing With the Ubiquitous Growth of Big Data

Big_Data has become the ubiquitous catchphrase for the collection and analysis of massive batches of data. With huge volumes of data residing on the enterprise servers, and the same growing by leaps and bounds, enterprises are looking at various ways to optimize all their big_data. Big_Data has brought about a paradigm shift in the way industry looks at storing and consuming data. However, mining millions of rows of data creates a big challenge for analysts tasked with sorting and presenting data. Enterprises today have to deal with managing and analyzing exponentially growing data, both structured and unstructured coming from various sources.

With terabytes and petabytes of data pouring into organizations today, traditional architectures and infrastructures are not up to the challenge. The main challenge of all IT teams is to understand and use big_data when it comes in an unstructured format, such as text or video, and capture the most important data as it happens and deliver that to the right people in real-time. Besides the numerous other challenges, from the privacy and security of access and deployment, enterprises also face the challenge of processing these large amounts of unstructured data quickly enough to make it useful and relevant to their business.

As the big_data landscape continues to evolve, it has become necessary for organizations to plan initiatives and carefully select the right tools to help decision-makers meet long-term goals. Hastily taking on big_data projects are more likely to result in unnecessary difficulties and potentially hinder a firm from succeeding. Enterprises today are looking to quickly deploy advanced and powerful capabilities of analytics platforms for faster and more complex processing to gain more value from this data.

Understanding what big_data is and how it can move your organization forward is of utmost significance, as it is important to find business value in that information. CIOs are looking to turn their enormous organizational data into actionable information; they should ensure that applications must be able to analyze potentially enormous volumes and varieties of continuous data streams to provide decision makers with critical information almost instantaneously. Organizations develop detailed metrics to assess their big_data application including the time required to turn data into insight, to integrate new and existing information sources, to manage the data and the value derived achieved from the data. Big_data holds the key to the critical information an organization needs to attract and retain customers, grow revenue, cut costs, and transform business.