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Innovation Beyond The Four Walls

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FEATURED NEWS

January, 27, 2016

Cognizant Acquires KBACE Technologies to Enable Clients to Accelerate Journey to Cloud and Improve Business Agility

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The Cognizant Difference

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BIG DATA ANALYTICS

We live in a world of data abundance, but are underwhelmed by paucity of insights. The sheer complexity of storing and indexing large data stores, as well as the information models required to access and make sense of them, is burdensome to all companies, regardless of size and industry. Uncovering new insights from big data – contained in both structured (transactional) data and unstructured/semi-structured (interactional) formats -- requires prioritizing, organizing and validating on the back end and employing front-end analytical tools that are accessible to knowledge workers. It’s bigger than merely changing out technology; it also requires a delicate overhaul of key knowledge processes to ensure that signal is applied and noise is discarded.

A well-executed big data program provides the opportunity to uncover hidden markets, reveal unmet customer needs and cost savings opportunities and drive game-changing, meaningful improvements in everything from shipping efficiencies to medical treatments, to social media campaigns and related digital marketing promotions.

BEST PRACTICES

Our work with leading clients worldwide reveals the following big data analytics best practices:

  • Establish processes and organizational structures, then choose the best tools to solve high-value business problems.
  • As you experiment, continuously refine existing processes -- and create new ones -- and acquire tried and true tools to support big data. Be cost conscious, of course, but focus primarily on agility and speed of decision making, as well as ease of use by non-technical knowledge workers.
  • Don’t underestimate the importance of master data management. The need for a single version of truth is especially true for big data analytics initiatives.
  • Train your staff in the databases, technologies and ontologies required to build, manage and extend big data capture and subsequent analysis. If you lack big data analytics skills, you are not alone. Consider analytics as-a-service to provide a cost-effective, standardized way of supplementing internal talent and adding horsepower to prosper from big data analytics.

A more virtual and globalized world requires businesses to work proactively and anticipate change before it happens. Big data analytics can help businesses meet this challenge, but only if they align tools, processes and organizational structures to advance operational agility and deliver business results.

  • Our Latest Thinking

MDM and Social Big Data: An Impact Analysis
By combining social big data with master data management, businesses can develop personalized products and services, anticipate customer needs and gain competitive advantage.
Personalizing Search
By applying user context and uncovering essential information, search engines can deliver a more rewarding experience, resulting in more digital revenue for the organization.
In-Memory Computing: Powering Enterprise High-Performance Computing
In-memory computing (IMC) is a vital hyperscale technology that enables enterprises to achieve high-performance computing and handle massive data management tasks. We offer a roadmap for evaluating available IMC options and determine which IMC package is best suited to your organization's needs, current and future.
How Airlines Can Deliver a Personalized Customer Experience During Operational Disruptions
By creating 'personas,' airlines can determine how and where customers want to engage and customize offers that secure loyalty and elevate brand reputation.
Leveraging Anonymized Patient Level Data to Detect Hidden Market Potential
Longitudinal analysis of anonymized patient level data (APLD) is a powerful tool for assessing patient experience on a granular level that will lead to better treatment outcomes and increased life sciences market penetration.
A Holistic Approach to Property Valuations
A brief guide to incorporating all available data, structured and unstructured, in the property valuation activity, by choosing key variables and running textual analysis.
From Relational Database Management to Big Data: Solutions for Data Migration Testing
Big data migration testing for transferring relational database management files is a very time‑consuming, high‑compute task; we offer a hands‑on, detailed framework for data validation in an open source (Hadoop) environment incorporating Amazon Web Services (AWS) for cloud capacity, S3 (Simple Storage Service) and EMR (Elastic MapReduce), Hive tables, Sqoop tools, PIG scripting and Jenkins Slave Machines.
Creating a Banking Experience that Keeps Customers Coming Back
Today's customer experience is part digital, part physical. Here's how your bank can use customer insights to better engage customers and prospects and create seamless, consistent experiences at every touchpoint.
Synergizing Master Data Management and Big Data
Master data management (MDM) is key to organizing, standardizing and linking volumes of big data that characterize today's information-driven environments. Understanding how MDM and big data inform and complement one another can offer organizations deeper, more actionable insights and a "single version of the truth" to support better decisions and realize new competitive advantages.
Driving Process Excellence through Intelligent Automation across the Contract Management Lifecycle
By adding intelligent automation to the contract management process, organizations can improve contract search, retrieval and management, drive cost savings, speed processing, boost compliance and reduce risk.
 

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