Big Data Analytics - Bodhtree, a leading data analytics services provider offers solutions that can help organizations capitalize on the transformational potential of Big Data and derive actionable insights from their data.

1. Big Data: Challenge or Opportunity?
Consider a simple example of going for a movie with your family: you send a tweet that you are going
for a movie and create data; you browse through the list of movies and theatres and access data; you
purchase tickets online and create data; you fill fuel on your way and swipe your card to pay, and create
data; you post a review on the movie on Facebook and create data.
Just as you create and work with data throughout this activity, your credit card company, the movie
theatre and fuel station also juggle with terra bytes of business and customer data on a daily basis.
While this data can pose several challenges for businesses, it creates opportunities for organizations to
gain insight into their customer's buying preferences and choices.
According to a recent research report published by Gartner, Big data forces businesses to wrestle with
three key strategic and operational challenges: Information Strategy, Data Analytics and Enterprise
Information Management.
Here is a more detailed explanation from Gartner on each of these operational challenges. These
illustrations can benefit our customers when they formulate big data strategies for their organizations. I
would highly recommend all of us to read these explanations and use these references while answering
big data related questions we face from our customers.
Information Strategy
Enterprises need to harness the power of information assets. Big data is causing enterprises to find new
ways to leverage information sources to drive growth. When trying to identify ways in which their
enterprise can benefit from big data and why it's important, they need to make the strategic decisions
that will transform their business.
Strategy: Is their organization prepared for an information-led transformation? How will they harness
big data to improve strategic decision making? They need to know which investments will deliver the
most business value and ROI.
Governance: How will they govern their organization's information assets in support of their enterprise
information management (EIM) goal? Are there new expectations for information quality and
management?
Talent: By 2015, Gartner predicts that 4.4 million jobs will be created around big data. Does their
organization lack the "data scientist" talent required to exploit big data? How will they assemble the
right teams and align skills?
Data Analytics

2. Businesses need to draw more insight from big data analytics or large and complex datasets. They need
to predict future customer behaviors, trends and outcomes. IT is under pressure to tap into growing
quantities of data to help the business make better, informed decisions by combining new sources of big
data with existing enterprise dark data. How will they uncover more customers and business insight and
more data value?
Predictive Analytics: How are they using data for predictive and real-time analysis across various
business domains? How can they use unstructured enterprise information and data to drive a better
client experience? How are they leveraging new data types: sentiment data, clickstream data, video,
images and text data?
Behavioral Analytics: How will they tap into complex data sets to create new models to drive business
outcomes, decrease costs, drive innovation or improve customer satisfaction?
Data Interpretation: What new business analysis can be drawn from their data? How will IT help
support insight discovery and new information trends? They need to know which data to integrate for
new product innovation.
Enterprise Information Management
Information is everywhere - volume, variety, velocity - and it keeps growing. Organizations need to
manage access to growing extreme information management requirements and drive innovation in
rapid information processing. What are they doing with all of the data the organization collects? They
have many disparate sources - from their enterprise's "dark data" and partner, employee, customer and
supplier data to public, commercial and social media data - that they need to link and exploit to its
fullest value:
User expectations: Employees are demanding more access to big data sources. What's their plan to
manage access to these information sources? What are the use cases?
Costs: How can they deliver access to big data in a rapid and cost-effective way to support better
decision-making?
Tools: How will they link these new sources of diverse data? They need to plan the impact on the data
center. Have they identified the processes, tools and technologies they need to support big data in their
enterprise?
Mckinsey calls big data "the next frontier of innovation". Evidently, the challenges with big data are
limited when compared to the opportunities it creates and the potential benefits it offers. Our creativity,
knowledge and ability to contextualize and understand this data is key to deriving value from it.