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5 Steps to value: Big Data Discovery

Francis Han, General Manager, ASEAN, Business Analytics, Oracle | April 24, 2015
Oracle ASEAN's Francis Han on how big data is poised to reshape industries- ranging from healthcare to retail to financial services.

Francis Han  - Oracle

Photo - Francis Han, General Manager, ASEAN, Business Analytics

This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.

No doubt that Big Data is the one single trend that will significantly reshape industries- ranging from healthcare, retail to financial services.

However, actual users on the ground are still faced with challenges. For one, enterprises have been using Hadoop to collect colossal amount of data. But how do they make sense of what they have collected?

Here are five challenges and the Big Data discovery solutions that the market now offers to combat these challenges.

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 centre 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.

Utilising 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, this 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 sentiment buried in the raw text.

Rather than spending 80 percent 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 for 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 to 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 service.
5) Share: Drive Collaboration
Big Data Discovery solution fulfils 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.
 Big Data: The Value Is Now
With Big Data Discovery solutions, companies can rapidly turn raw data into actionable insights without relying solely on specialised 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 the 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.

 - Francis Han, who is General Manager, ASEAN, Business Analytics, for Oracle Corporation, sourced material from: oracle/us/products/oracle-big-data-executive-brief-2415577.pdf


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