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Big Data Strategy of IBM

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Case Details:

Case Code : ITSY076
Case Length : 18 Pages
Period : 2010-2013
Organization: IBM
Pub Date : 2014
Teaching Note : Not Available
Industry : Information Technology streaming services
Countries : US; Global

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This case study was compiled from published sources, and is intended to be used as a basis for class discussion. It is not intended to illustrate either effective or ineffective handling of a management situation. Nor is it a primary information source.

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Big Data And Analytics Origins

According to the Oxford English Dictionary, the term ‘Big Data’ was first used in 1941 to quantify the growth rate in the volume of data – alternatively known as the information explosion. In his article, The Scholar and the Future of the Research Library (1944), Fremont Rider, a Wesleyan University librarian, estimated that in every 16 years, the university libraries in US doubled in size. He used the term Big Data to refer to this increase. In 1967, in an article called Automatic data compression published by BA Marron and PAD de Maine, the term was used for the first time to indicate the information explosion on external storage devices through computers. Later, the term became more and more related to information in the digital format and the Information Technology sector. ...

IT and Systems Case Studies | Case Study in Management, Operations, Strategies, IT and Systems, Case Studies

IBM And Big Data

In the 1950s, John Hancock Mutual Life Insurance Co. collected 600 Megabytes of corporate data. This was the largest amount of corporate data collected till then. The company was one of the pioneers of digitization. It collected and stored information of two million policy holders on a Univac computing system. During the 1960s, American Airlines developed a flight reservation system using IBM computing systems and stored around 807 Megabytes of data. Federal Express, with its scanning and tracking, collected 80 Gigabytes of data during the 1970s. In the 1980s, with its focus on analyzing ATM transactions, CitiCorp., gathered 450 Gigabytes of data....

Big Data Strategy

Smarter Planet was a corporate initiative of IBM, which sought to highlight how government and business leaders were capturing the potential of smarter systems to achieve economic and sustainable growth and societal progress. In November 2008, in his speech at the Council on Foreign Relations, IBM’s Chairman, CEO and President Sam Palmisano, outlined an agenda for building a ‘Smarter Planet’. He emphasized how the world’s various systems – like traffic, water management, communication technology, smart grids, healthcare solutions, and rail transportation – were struggling to function effectively....

IBM'S Big Data Platform

IBM committed itself to Big Data and Analytics through sustained investments and strategic acquisitions. In 2011, it invested US$100 million in the research and development of services and solutions that facilitated Big Data analytics. In addition, it had been bringing together as many Big Data technologies as possible under its roof. The Big Data strategy of the company was to combine a wide array of the Big Data analytic solutions and conquer the Big Data market. The company’s goal was to offer the broadest portfolio of products and solutions with the depth and breadth that no other company could match.......

Addressing Emerging Business Requirements

In 2013, IBM was awarded the contract to support Thames Water Utilities Limited’s (Thames Water) Big Data project. The UK government planned to install smart meters in every home by 2020. Using these meters, the company would be able to collect a lot of data about the consumption patterns of its customers. As a part of its next five-year plan, Thames Water planned to invest in Big Data analytics to improve its operations, customer communication, services, and customer satisfaction using this data. It chose IBM as an alliance partner for the project to support technology and innovation......

Big Data Challenges

Over the years, consumer attention had shifted from radio, print, and television to the digital media as it facilitated real-time engagement of consumers. Brands competed for consumer attention through such media and relied on them for data and analytics for customer acquisition and retention and to offer tailor-made products and services to them. However, some analysts believed that relying on such data was a mistake. They said the real challenge with such data was that it was mostly unstructured and the difficulty lay in structuring it and filtering the genuine data....

Addressing Challenges

IBM had brought in new systems, software, and services to complement its Big Data platform. With these products it helped its customers to access and analyze data and use it to make informed decisions for the betterment of their businesses. The Big Data solutions were also meant to protect data and identify and restrict suspicious activity and block access to company data....

Looking Ahead

In the past few years, Big Data had been the most hyped technology trend, and by 2013 it had started to gain acceptance as it held promising opportunities for businesses. It was showing its impact on the healthcare, industrial, retail, and financial sectors to name a few. It enabled companies to run live simulations of trading strategies, geological and astronomical data, and stock brokers could analyze public sentiment about a company from social media. Emerging technologies such as Hadoop, NoSQL, and Storm made such analytics possible. According to a Gartner survey in 2013, 64% of organizations had invested or planned to invest in the technology, but only 8% of them had actually begun deployment. Many businesses were in the process of gathering information as to which business problems Big Data could solve for them. ...


Exhibit I: A Brief Note on Big Data
Exhibit II: IBM’s Products and Services
Exhibit III: IBM’s Financial Data (2008-2012)
Exhibit IV: IBM’s Important Big Data Acquisitions
Exhibit V: Capabilities of IBM’s Big Data Platform
Exhibit VI: IBM’s Big Data Portfolio of Productse
Exhibit VII: Problems Addressed by IBM’s Big Data Solutions


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