Big Data Challenges and Opportunities: Harnessing Big Data
Data is an organization’s lifeblood. Without it, an organization can’t function. But data is expanding faster than ever and now we’re facing big data challenges too: not just large volumes, but data that changes rapidly, comes in more varieties and from more sources. Structured, internal data is increasingly being supplemented by unstructured data like audio, video and sensors, and data from external sources like the internet, social media and third parties.
The big data opportunities for gaining valuable new insights by blending and analyzing the multiple datasets is enormous; at the same time, the challenges of big data are to store, protect and handle data appropriately, to prevent it from becoming a liability. With big data opportunities come big data challenges.
How organizations find and use data as an asset is changing dramatically. A data-driven economy is emerging, and organizations are beginning to understand and explore the big data opportunities. With so much data becoming available the challenge is harnessing big data in new ways and maximizing the business value it can deliver.
Until recently, it wasn’t possible to interrogate unstructured data, like email and conversations, in conjunction with structured data, such as spreadsheets and databases. But now it’s becoming easier to combine and analyze vast, rapidly changing datasets, using new technologies and techniques that can mine it in more meaningful ways than before.
The prospect of gaining fresh insights from the new datasets is exciting: if you could generate actionable intelligence, that’s delivered to the right people at the right time, your organization could acquire an important competitive edge and even transform the business. But where do you start, when there is simply so much data that’s changing and growing all the time?
Big Data Challenges & Opportunities: Harnessing Big Data
The onset of big data introduces a world of opportunities to harness big data as an asset. Finding new insights by blending and analyzing internal and external data transforms data into a valuable asset for your organization. For example, if an analysis enables the prediction of which customers might defect to a competitor, actions can be taken to prevent that from happening.
Suppose a mobile phone company’s customer posts on their social networking site that they’ve switched to another provider and have a great new handset and call plan. That could persuade others to switch to that provider as well. If the phone company can see who those friends are and match them to its customer records they can quickly take action with an attractive offer to retain the valuable customers before it’s too late.
On the other hand, big data challenges can be a liability if data is not stored appropriately, or worse if your data gets accidentally or maliciously shared with the competition.
Why Is Data so Often an Under-Utilized Asset?
We all understand the value of data, in a theoretical way at least. So why don’t we exploit it to the full? One of the most common problems of big data is the quality of the data. If an organization’s data is variable, inconsistent or incomplete, the insight it could yield becomes suspect, and the organization might not want to risk acting on it.
Even if there are no issues with the quality of the data, an organization might not have the right tools to analyze the content in a meaningful way; or might not be able to deliver the data in a timely manner to the right person. In addition, combining your own data with external sources will increase the potential for fresh insight.