How to Increase the Value of Business Data in 2018

How to Increase the Value of Business Data in 2018

The economics of data are changing. Data is driving business acceleration by enabling smarter, near-real time decisions based on Fast Data, and the ability to extract insight and trends from archived Big Data. For digital transformation to happen, data needs to come alive, and to fully benefit from its potential, it needs to be as rich with information as possible, and it needs to live forever.

As businesses rethink how data is captured, preserved, accessed and transformed, what steps can they take to see more value from their data in 2018? 

[Tweet “How businesses can increase the value of their #data in 2018 #digitaltransformation”]

What steps can businesses take to see more value from business data in 2018?

Getting to the goal of insight should be the primary focus of businesses. The following steps, if not already taken, are imperative to get to insight:

  1. Get any remaining archive data off of tape. It is nearly impossible to make data accessible if it is on tape. This doesn’t mean eliminating tape, but it does mean that at least one copy of data needs to be on some kind of online media.

Recommended read: Moving From Tape To Cloud? 5 Things You Need To Do First!

  1. Enable hybrid cloud so that apps can be run in the public cloud for agility and responsiveness, but massive data can rest protected in a cost-effective solution on-premises. The quickest way to enable analytics is to run them in a public cloud. Many public cloud providers come with built in analytics and databases. However, the best place to store your long-term assets is still on-premises. The hard work will be in solving the data movement challenge to get the right data into the public cloud for processing with analytics.

Recommended read: The Big 5 – Hybrid Cloud Insights

  1. Start thinking about building data lakes instead of data archives so that the data is “analytics ready”. Data lakes are archives that have additional services such as index and search, and data tagging, as well as well-defined interfaces to analytics services such as Apache Hadoop® and a range of in-memory databases. With data lake capabilities in place, the step to analytics can be a small one.

Recommended read: Building a Better Data Lake with Apache Hadoop® on Object Storage

  1. Focus on metadata. Getting value from data is as much about the metadata as it is about the data. Start thinking about adding metadata that is relevant to your business to your data – either manually or automatically. It is hard to get value from data without first knowing about the data.

Recommended read: Digital Preservation 2020 – Start Your Metadata Thinking

  1. Stop using backup as a form of archiving. Archiving data in a backup format makes the data nearly useless if you want to see value from it. Data is not accessible if it is buried in a tar file. In addition, backup policies are not appropriate for lifecycle management of archive data. This is especially true today when data gets more valuable over time, not less valuable. Old data, when aggregated with new data, may be the most valuable data for machine learning and AI based analytics. Archiving is not about recovering entire data sets but rather preserving it and being able to access it using search and index techniques.

Learn how other companies are tackling digital transformation and the growth of unstructured data in our latest survey.


Related Stories