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Big Data: Challenging Conventional Models and Strategies

Ever-increasing requirements and capabilities to process gigantic quantities of business and social media data are influencing notable changes in information technology and business environments. This phenomenon is being described by industry professionals as Big Data and it is influencing product development, market and consumer segmentation, and promotional activities. Big Data is undoubtedly both an opportunity and a threat as the amount of online data is significantly increasing and the tools to manage and manipulate data growing expeditiously within the business and social media segments. Recent market research states that data is doubling every 18 months!

Big Data Definition

What is Big Data? The term describes the tools, processes and procedures enabling an organization to effectively, efficiently, and with flexibility create, manipulate, and manage large data sets and storage facilities. This includes terabytes, petabytes, exabytes, and zettabytes collections of data. Big Data is data generated from customer transactions and obtained from external research and data base providers that is growing so large that it is awkward and problematic to use with conventional data management approaches and tools.

The Big Data approach has been a valuable and evolving customized tool set over recent years among large credit card, communications, retail, and financial companies. For example, businesses like Amazon, EBay, AT&T, Capital One, Google, and VISA successfully manage huge databases that they mine for competitive advantage.

Big Data in most organizations can be compared to an ‘iceberg’ – frozen and somewhat underwater! The frozen state represents traditional corporate format and use standards that make it difficult to flow data throughout the organization. Data is considered underwater when for reasons of privacy, competitiveness, and / or incompetence data is hidden, off-limits and not totally shared with the employee universe.

A Big Data strategy typically includes: identifaction, adoption, and implementation of a technical solution set and; policies on the format and use of the corporate data. Development of a Big Data strategy generally begins at the point where executives get involved with problems associated with the technologies and approaches used to drive and manage their large enterprise data sets.

Big Data and SMB Market

Big Data analytics is no longer just on the radar screen of the Fortune level companies. Increasingly, Big Data and cloud computing in tandem is becoming attractive to small and medium business (SMB) companies. For these companies this technical combo provides high-level competitive capabilities to leverage the la carte economics of elastic computing and adopt a cost-effective Big Data approach to grow existing business and / or discover new product and market opportunities. Because cloud computing removes an upfront investment requirement for purchase of a costly infrastructure, SMB companies no longer face a significant financial barrier for creation of a Big Data strategy and implementation of an appropriate technical solution.

Big Data and Litigation

Attorneys and their clients increasingly face the dilemma of how to efficaciously conduct searches for relevant documents in large heterogeneous digital data sets, for the purpose of responding to court-order requests. Recent litigation experiences show that companies are being required by law to store large masses of content and documents, Email messages and other forms of electronic communication that may be necessary if they face litigation.

The unprecedented size, scale, and complexity of digital stored data now subject to routine capture present organizations with potential exposures ensuing from the failure to submit requested documents in full and on time to the court to avoid sanctions.

Big Data Technologies

Big Data is having a direct impact on web, cloud, enterprise, mobile platforms as many technology vendors are developing solutions to enable optimum management of large sets of data. The noteworthy Big Data challenges and requirements support the industry belief that no single technology will provide a silver bullet solution. Instead an array of technologies that are each focused on meeting specific set of requirements are improving our ability to manage data at scale. Emerging Big Data technologies and the high rate of their acceptance and use are testing conventional business models and strategies.

Key technologies currently the focus of the industry professionals in support of Big Data requirements include: MPP Analytics, Cloud Data Services, Hadoop & Map/Reduce (and associate technologies such as HBase, Pig & Hive), In-Memory Databases, some Distributed NoSQL database and some Distributed Transaction Processing databases.
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