Data Management: The Value of Structured and Unstructured Data
Data Management in organizations is crucial; as we have heard the quote multiple times, “Data is the new oil”. With the rise of next generation technology like artificial intelligence, machine learning, and predictive analytics, data has become the driving force behind every business and organization.
Data Management is a process of efficiently handling, organizing or being able to leverage large volumes of structured, historical data coming from a legacy systems, and unstructured data, coming from a variety of channels outside of the organization. This data fuels business decisions, applications and processes across every facet of the organization, providing a 360-degree view of the company. And as unstructured data expands in various forms, like VoIP, emails, text messages, and videos, so does the appetite to put it to use and understand the value it creates.
With the rise of social media in the last 10 years, businesses have been producing large amounts of inbound, unstructured data in various forms. Those who leverage this new channel attract new customers and retain the ones they have, while driving cost savings and efficiencies in how the business engages with their community. However, the result produces large volumes of unstructured data that can to be hard to evaluate when identifying insights on how to grow the business. Many organizations still struggle to manage it well.
The development of big data platforms, primarily Hadoop, NoSQL databases and the Amazon Simple Storage Service (S3) provide the required infrastructure for processing, storing and managing large volumes of unstructured data. Once contained, then organizations can layer on a variety of analytical techniques and tools to operationalize the value of their unstructured data.
Stay tuned for our next release around identifying, applying, and adopting the latest platforms and tools to gain the most value of structured and unstructured data, coming next month.