There is more data available today than ever before, but many organisations do not get the full value and business insight they need to run their businesses and stay competitive. So what is Big Data and how can it help organisations?
Introducing Big Data
Big Data is a term that describes the large volume of data – structured and unstructured – that inundates a business daily. But it’s not the amount that’s important. Big Data can be analysed for insights. And these lead to better decisions and strategic business moves. In recent years Big Data has changed significantly – new inputs like social media and the Internet-of-Things are increasing volume. Sales records, manufacturing reports and HR information which historically sat comfortably in silos, now need to be shared and correlated across functional areas and disparate applications. And businesses now need real-time decision support such as predictive data to help them make better decisions.
So… What’s the problem?
The systems of the past can no longer handle the barrage of inputs that companies collect and analyse in order to respond quickly to their business needs. Web-scale companies like Amazon actively utilise Big Data and analytics through their own proprietary infrastructure. But few companies have the scale to solve the problem in that manner. Most traditional storage systems were designed for structured data at terabyte scale. Today, instead of terabytes, we’re often talking about tens or even hundreds of petabytes. Mostly, unstructured data, with exabyte-scale coming soon. And collecting, storing, and managing data is only part of the solution. If it’s not easily accessible or properly integrated with the analysis element, then you haven’t really solved anything. Most businesses have enterprise data warehouse products to analyse structured data that exists in relational database management systems (RDBMS) but in today’s environment, this represents a small fraction of all enterprise data. Unstructured data like social media doesn’t fit within the RDBMS model.
Getting the most from data resources requires a rethink of the way an enterprise collects, processes, stores, manages, and analyses data. To stay competitive and meet new business demands in a more efficient way, IT needs to think differently about the systems they deploy for Big Data and analytics. Providing a better customer experience comes from gaining a deeper understanding of the customer. The more data that is available, the better the insight. The same is true when it comes to understanding how to serve each customer more cost-effectively. Thinking a bit differently about technologies like storage and compute should provide you with the ability to leverage server-based storage, optimise computing, and intelligently scale your infrastructure whilst extracting valuable insight from rapidly growing volumes of data. Learn more about how Hewlett Packard Enterprise is one of the few vendors truly innovating with new technologies that can help with Big Data.
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