Navigating the big data maze

By: Sundar Ram, Vice President, Technology Sales Consulting, Asia Pacific, Oracle

The big data landscape has been confusing, and organizations are struggling to collect, store, prepare, and analyze the data, let alone get insights out of it. In this context, here are five ways by which big data discovery solutions can help enterprises discover value out of big data.

#1 Find: Pinpoint Relevant Data
A retail analyst who wants to improve the results of a marketing campaign has lots of potential data to sift through—customer tweets, loyalty program details, contact center complaints, and more.
However, it isn’t easy to determine which of that data is timely and trustworthy. So, it is essential to find and pinpoint relevant data. Big data discovery solutions have allowed analysts to navigate the rich catalogue of all the raw data in a Hadoop cluster to quickly identify what’s relevant. Searching the data is as easy as shopping online.

#2 Explore: Understand Data Potential
Understanding the potential value of data consumes a lot of analysts’ time. For instance, an analyst for an auto manufacturer seeking to streamline its manufacturing processes would likely endure many false starts when exploring the mass of information related to the engine building process, from poorly scheduled lunch breaks to disconnect between suppliers. Utilizing big data discovery solutions can sort information potential, with the most interesting attributes appearing first.
In addition, analysts can easily experiment with different combinations of data to understand correlations, so they can rapidly determine whether the data set is worthy of more attention.
The system also helps them quickly get a handle on data quality and other key elements, preventing time and money from being wasted on projects with limited potential.

#3 Transform: Intuitive, User-Driven Data Wrangling
Typically, data in Hadoop needs to be manipulated and prepared before it can be used for analytics. Leveraging on big data discovery solutions, which use an intuitive spreadsheet-like approach will transform big data for use in analytics. At the same time, the data can be enriched to infer location and language or detect topics, themes, and sentiments buried in the raw text. Rather than spending 80% of their time on data preparation, analysts can quickly transform even massive volumes of big data, making it available for the entire enterprise and freeing them to spend the bulk of their time on analytics.

#4 Discover: Unleash Creativity
Discovering big data insights requires creativity, which can be difficult to hire or developed in-house. With big data discovery solutions, enterprises can get more out of their analytics talent through tools that automatically blend data for deeper perspectives and see new patterns in rich, interactive data visualizations. For example, if a telecom analyst wants to investigate the reasons for customer churn, he can use big data discovery solutions to mash up or join different data sets.
This will reveal a whole new perspective; for example, it might show that customers in a certain geographic region using a certain handset are cancelling their accounts because of a technical glitch that is disrupting the service.
#5 Share: Drive Collaboration
Big data discovery solutions fulfil the promise of democratizing big data analytics by enabling the results to be shared and published. Suddenly, information becomes a focal point of enterprise
collaboration and collective discovery. Teams can share projects, bookmarks and galleries of snapshots, enabling them to collaborate and iterate. Analysts, meanwhile, can publish their data transformation and enrichment results back to Hadoop, securing the work they’ve done to maximize the value of the data.
FINDING THE GOLDEN NUGGET
With big data discovery solutions, companies can rapidly turn raw data into actionable insights without relying solely on specialized talent. They can extend the alchemy of big data to more people
in the enterprise, creating entire teams that work collectively on insight discovery, improving efficiency, and extending the expertise of their existing analytics staff.
In short, businesses now have a platform that can enable their own transformation; they can embrace analytics and use new insights hidden in big data to make strategic and game changing decisions quickly, ensuring their success well into the future.