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Analytic

Technology makes it economically viable to mine information to create new insights and better inform your future decisions.

Whether they're records kept in spreadsheets and log files, information embedded in photos, videos, tweets and emails, or streams of data from connected devices, sensors and machines, we've been surrounded by vast quantities of data for a long time. Now it has a name — big data.

Competitive and market pressures have transformed that information into a new competitive opportunity. The insights and trends hidden in these many sources of structured and unstructured data offer the chance to draw new distinctions between you and your competitors.

In an increasingly quantitative, digital world, everything is, or will be, recorded or counted. You need to find value in that data, spotting the seemingly unrelated patterns in data, mining and refining it, to create insights with commercial value. Business Analytics is the solution that turns the promise of big data into a source of practical, continuing insights to improve organizational performance.

Analytics

Analytics is more than just another app

Tapping the power of big data goes beyond the usual IT improvement exercise. The benefits of big data are realized when you understand how to derive new ideas from so much information and how to execute business decisions based on these insights. It involves change in your company and business processes that can drive deep into the organization. New structures and processes are needed to ensure the quality of data, so you can trust what it reveals. Your IT department must evolve from serving as an enforcer of systems to being a trusted information provider. You need to know how to use analytics that create genuine insights, not false leads. And, you need the right kind of organizational structure to make the most of what you learn.

An investment in analytics will grow in value and utility.

The expected growth in data is nothing short of astounding, from 800,000 petabytes of digital information in 2009 to an estimated 35 zetta bytes in 2020, a 44-fold increase. Still, a recent Economist Intelligence Unit report revealed that many companies have yet to tap that potential. Half of the business leaders who responded have yet to gain access to this growing asset. 80% of CIOs cited business intelligence and analytics as part of their plans to enhance competitiveness.

Join the ranks of companies fueling their growth using analytics.

Some organizations are already reaping the benefits of an investment in business analytics.

One of the world's leading mining companies is extracting value from the masses of data from sensors and equipment to improve operational plans that affect people, equipment and maintenance. Combining insights from this data with organizational and procedural change, the company is lowering operating costs while improving safety.

Avis Budget, a leading car rental agency, is using analytics to learn who their best customers are, and what they really value — an approach that is creating substantial top-line and bottom-line benefits. The company's move to establish an analytics-driven marketing organization demonstrates that business change has to go hand-in-hand with the technology to lead to real results.

How would your business benefit if you could connect the dots between the pools of data that have surrounded you for years? What trends remain hidden which, if brought to light, could propel your company into a new category of growth?

Take steps to implement a business analytics solution.

Implementing business analytics to capitalize on big data requires the engagement of every part of your organization. Changes in IT must be matched by organizational change because you won't get value from what you learn about your business if you aren't structured to take advantage of it. That approach should include:

  • Plan — Create a detailed project plan first. Gather resources and inputs, assemble the team of business and IT skills, and ensure that the sponsorship and communication is in place and effective.
  • Discover — Build an analytic development environment to develop, test and refine an initial set of analytics. Initial results allow you to assess the business impact and make recommendations. Early success will ensure that sponsorship and buy-in stays strong across the organization.
  • Act — Execute the plan using technology so you can make use of your big data insights.
  • Embed — Embed the analytics capability into the organization. This will include potentially far-reaching changes to processes, people, organization, data, applications and technology.

Business Analytics

Business Analytics Solution

Business Analytics Implementation service will guide you through the business change you need to successfully implement analytics for big data and if you would like further help, we can manage and deliver your organizations ongoing business analytics requirements through our Business Analytics-as-a-Service.

Wherever you are in your use of business analytics and big data, we can help your business and IT department lead your company to a higher level of sophistication in the use of data-based insights. Contact us today to learn more.

Hadoop Use Cases

Diagnostics and Customer Churn

Issues

  • What make and model systems are deployed?
  • Are certain set top boxes in need of replacement based on system diagnostic data?
  • Is there a correlation between make, model or vintage of set top box and customer churn?
  • What are the most expensive boxes to maintain?
  • Which systems should we pro-actively replace to keep customers happy?

Big Data Solution

  • Collect unstructured data from set top boxes—multiple terabytes
  • Analyze system data in Hadoop in near real time
  • Pull data in to Hive for interactive query and modeling Analytics with Hadoop increases customer satisfaction

Pay Per View Advertising

Issues

  • Fixed inventory of ad space is provided by national content providers. For example, 100 ads offered to provider for 1 month of programming.
  • Provider can use this space to advertise its products and services, such as pay per view.
  • Do we advertise “The Longest Yard” in the middle of a football game or in the middle of a romantic comedy?
  • 10% increase in pay per view movie rentals = $10M in incremental revenue

Big Data Solution

  • Collect programming data and viewer rental data in a large data repository
  • Develop models to correlate proclivity to rent to programming format
  • Find the most productive time slots and programs to advertise pay per view inventory
  • Improve ad placement and pay-per-view conversion with Hadoop

Risk Modeling

  • Bank had customer data across multiple lines of business and needed to develop a better risk picture of its customers. i.e., if direct deposits stop coming into checking acct, it’s likely that customer lost his/her job, which impacts creditworthiness for other products (CC, mortgage, etc.)
  • Data existing in silos across multiple LOB’s and acquired bank systems
  • Data size approached 1 petabyte

Why do this in Hadoop?

  • Ability to cost-effectively integrate + 1 PB of data from multiple data sources: data warehouse, call center, chat and email
  • Platform for more analysis with poly-structured data sources; i.e., combining bank data with credit bureau data; Twitter, etc.
  • Offload intensive computation from DW.

Sentiment Analysis

  • Hadoop used frequently to monitor what customers think of company’s products or services
  • Data loaded from social media sources (Twitter, blogs, Facebook, emails, chats, etc.) into Hadoop cluster
  • Map/Reduce jobs run continuously to identify sentiment (i.e., Acme Company’s rates are “outrageous” or “rip off”)
  • Negative/positive comments can be acted upon (special offer, coupon, etc.)

Why do this in Hadoop?

  • Social media/web data is unstructured
  • Amount of data is immense
  • New data sources arise weekly