Cognizant BigFrame Fast, Secure Legacy Migration Speeding Business Access to Critical Data BigFrame speeds migration from legacy systems to secure next-generation data platforms, providing up to a 4X performance improvement at 60 percent lower cost. It slashes the time, cost and complexity of migrating data and the associated management processes. BigFrame reduces operations costs, meets performance benchmarks and surpasses business goals through real-time queries, advanced analytics and machinelearning insights.
Data is useless if it is locked in a legacy system that cannot scale, readily share data with other systems or is too expensive to operate. UNLOCKING THE POWER OF DATA Data fuels today s digital businesses. It powers insights into new ways to cut costs and increase sales. It creates new revenue streams through the sale of the data generated by people and devices. It can even create entirely new business models and industries, such as the real-time customization of financial products based on a customer s banking history or faster, more accurate underwriting of insurance policies, reducing portfolio risk. But such data is useless if it is locked in a legacy system that cannot scale, readily share data with other systems or is too expensive to operate. All too often, traditional mainframes or legacy data warehouses keep businesses from seeing and seizing opportunities more quickly and costeffectively to stay competitive in their industry. Data Warehouse Re-platform at ease BigFrame is Cognizant s prebuilt, proven migration engine that facilitates modernization of existing data appliance, warehouses and mainframe systems to maximize performance and reduce costs through automated optimization and migration bringing about 4x performance improvement and more than 60 percent reduction in effort. WHY MIGRATE WHY BIGFRAME GUI-enabled automated data and schema migration Lower implementation cost and greater flexibility Automated translation of queries and processes to target platform $ Reduced time-to-market Multi-threaded parallel execution with throttling High Total Cost of Operations (TCO) of existing data warehouse Legacy platform cannot scale to handle data flow velocity and volume Failure to meet performance benchmarks for data management and analytics Business cannot effectively utilize data to meet revenue, cost and profitability goals User friendly GUI to define, schedule and monitor migration processes Supports variety of targets on AWS, Azure and on-premise or cloud-based Hadoop Automated data validation with exception and metadata reports Enterprise data warehouse offload module built on open source stack, no need for licensed software Mainframe offload module uses Syncsort technology to speed data processing and seamlessly integrate mainframe data and processes with Hadoop Zero BigFrame software footprint post implementation, reducing ongoing costs Volume based license model matches costs to specific needs Figure 1. Why Cognizant BigFrame Cognizant BigFrame Solution Overview 2
THE LIMITS OF LEGACY SYSTEMS As organizations seek to exploit massive new data streams, legacy mainframes and data warehouses often become too expensive and slow to keep up. Neither can cost-effectively scale to meet the rising business need for information, quickly access archived data or combine data from multiple sources to provide a real-time 360 view of customers, markets and processes. Mainframe data processing costs, including software licensing and support, can run millions of dollars per year, while storage directly attached to the mainframe is also far more expensive than current cloud-based or Hadoop solutions. Mainframes running business-critical applications may have only limited processing windows available for batch analytic jobs. The high latency of mainframe archiving solutions such as tape increase the time it takes to retrieve historic data such as equipment maintenance records to perform proactive maintenance and prevent breakdowns. Legacy data warehouse platforms can become unacceptably expensive as organizations upgrade them to meet rising data volumes and analytics needs. They are also sometimes unable to effectively share and process data from all the sources required for today s big data requirements, such as social media and Internet of Things beacons and sensors. Moving to the cloud and open-source data management frameworks and software, as well as to cloud platforms such as Microsoft Azure and Amazon Web Services, can meet all these challenges. The public cloud dramatically reduces capital and operational costs by offloading the maintenance of the underlying compute, storage and network infrastructure to the cloud provider, spreading costs across customers and making management less expensive with automated tools. Use of the cloud also means the business pays only for the capacity it needs when it needs it, eliminating the requirement to buy and maintain enough hardware or software to meet peaks in demand. As a business grows or requires more analytics capacity, the cloud eliminates the wait for a vendor to ship, and the IT staff to install and configure, additional on-premise hardware and software. Open source data processing platforms such as Hadoop are not only much less expensive than proprietary tools, but let businesses tap a deep reservoir of prebuilt add-ons that extend the usefulness of these platforms, as well as a broad range of professionals skilled in their use. But migration to the cloud and such open source platforms can be expensive and time-consuming, requiring weeks or even months of manual work by specialized staff. Choosing the right partner and using proven and automated migration solutions reduces risk, costs and delays in moving data to a modern data platform. Use of the cloud also means the business pays only for the capacity it needs when it needs it, eliminating the requirement to buy and maintain enough hardware or software to meet peaks in demand. Cognizant Cognizant BigFrame BigFrame Solution Solution Overview Overview 3 3
HOW BIGFRAME AUTOMATES MIGRATION BigFrame, Cognizant s prebuilt, proven migration engine, makes it faster, easier and less expensive for companies to migrate data, workloads and data management processes from data appliances, data warehouses and mainframes to the cloud or to modern platforms such as Hadoop, either on the cloud or on-premise. Our automated processes deliver a four-fold performance improvement by aiding the migration to new cloud big data platforms with a 60 percent reduction in the effort required for the move. BigFrame provides must-have capabilities in the following three key areas for a successful data migration: Data Ingestion: An intuitive graphical user interface makes it easy to define, schedule and monitor the migration of massive amounts of data and their associated schema. Customers only need to identify the source and target systems, avoiding complex and time-consuming custom coding. BigFrame s multi-threaded parallel execution provides data offload speeds of up to 250 gigabytes per hour. It supports the replication and transformation of schemas and data definition languages and supports universal character sets such as UTF8, ASCII and EBCDIC as well as Web-based control Customer Story: Life Sciences Saving Millions, Speeding Data Access To reduce IT running costs while providing faster, more flexible access to data, a life science company needed to retire several mainframe applications and migrate their vast repository of global human health data to the cloud. BigFrame offloaded 25 terabytes of EBDCIC data at speeds of up to 5 gigabytes per minute and automatically created new tables using the target data definition language and schema. This migration is saving the company $3 million per year in hardware, software and support, reducing mainframe data hosting costs by 95 percent. It has also cut data access and retrieval times by 50 percent and reduced its dependence on IT with custom reports via enhanced self-service features, helping ensure their global regulatory compliance. Our automated processes deliver a four-fold performance improvement by aiding the migration to new cloud big data platforms. Cognizant BigFrame Solution Overview 4
features. It automates more than 90 percent of data ingestion and more than 85 percent of schema and table migration. Data Validation: BigFrame cuts the time required to move from data-capture to business-changing analytics with automated validation of the migrated data and an optimized data comparison tool. Our integrated testing engine reduces the effort required for validating data flows among source and target systems after migration by 40 percent, further speeding the time to business value. Process Translation for Teradata Warehouses: BigFrame s Translator module automates 70 percent of the migration of SQL statements and procedures from Teradata warehouses to target systems. BigFrame makes it easier to find, collect and analyze all the data a business needs with support for the migration of Teradata BTEQ and macros to SQLDW to support transaction handling, error handling and various procedural syntaxes. BigFrame s Translator module supports popular public clouds with the ability to convert Teradata SQL to the RedShift SQL used by Amazon s cloud-based data warehouse solution as well as private clouds and on-premise Hadoop, Cloudera and MAPR implementations, among others. Migration Requirement Manual Migration Automated BigFrame Migration Reusability Support for Multiple Enterprise Data Warehouse (EDW) Sources Support for Mainframe Data Sources Testing and Validation Intuitive GUI Teradata Process Translation Parallel Execution Build customized solution for each source and target Create a manual process to migrate each data source to the required targets Requires complex manual conversion All testing requires manual effort Customer creates their own graphical user interface to manage and monitor the migration Requires complex manual conversion Only one process performed on one file at a time Prebuilt standard components are usable for most common sources and targets Automated conversion of Teradata, Exadata, Netezza and other data warehouses enabled through prebuilt EDW offload module Supports ASCII conversion of all mainframe data types through our prebuilt offload module BigFrame s integrated testing engine enables automation of 40 percent of the testing process BigFrame s highly interactive GUI significantly reduces migration times by eliminating the need for coding. Comprehensive monitoring functions and dashboards make it easy to track the migration while it is in process BigFrame s Translator automates 75 percent of the migration of components such as Teradata SQLs and BTEQs to target platforms Logically related files can be grouped and transformed in a single process Figure 2. How BigFrame Saves Time and Money Over Manual Migration Cognizant BigFrame Solution Overview 5
Customer Story: Insurance A leading insurance company needed to dramatically reduce the cost of running applications that support a significant part of its business. These support functions such as claims processing, the sharing of member eligibility data with third parties and reports for business analysts. BigFrame migrated more than 100 terabytes of data from on-premise platforms to less expensive, faster cloud platforms and implemented a continuous integration, continuous deployment process (CI/CD). The continuous integration and deployment of logical groups of data and tables, along with the associated end-toend testing, allowed the insurer to realize incremental business value by accessing subsets of data as well-defined milestones in the implementation plan were reached. The automated migration process reduced operating expenses by 50 percent, saving the insurer $1.5 million per year, while providing a more scalable platform for the analysis of large quantities of legacy data for purposes such as fraud detection. The new platform also provides automation to more cost-effectively control, scale, secure and deploy infrastructure resources. Cognizant BigFrame Solution Overview 6
LEARN MORE Every day, organizations struggles with siloed, expensive and slow data management systems. But the journey to a modern engine can be seamless and clear. Companies can significantly reduce costs and scale their systems to support changing business conditions by migrating off their legacy systems. That migration, which allows the processing of their data on a cloud-based or on-premise big data platform, can be automated using BigFrame. Speed your move to a more efficient and scalable next-generation data platform and improve decision-making through real-time queries, advanced analytics and machine-learning insights with Cognizant s BigFrame. To learn more please visit - https://cognizant.com/cognizant-digital-business/ applied-ai-analytics/bigframe Cognizant BigFrame Solution Overview 7
1 ABOUT COGNIZANT Cognizant (Nasdaq-100: CTSH) is one of the world s leading professional services companies, transforming clients business, operating and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant is ranked 195 on the Fortune 500 and is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com or follow us @Cognizant. World Headquarters 500 Frank W. Burr Blvd. Teaneck, NJ 07666 USA Phone: +1 201 801 0233 Fax: +1 201 801 0243 Toll Free: +1 888 937 3277 European Headquarters 1 Kingdom Street Paddington Central London W2 6BD England Phone: +44 (0) 20 7297 7600 Fax: +44 (0) 20 7121 0102 India Operations Headquarters #5/535 Old Mahabalipuram Road Okkiyam Pettai, Thoraipakkam Chennai, 600 096 India Phone: +91 (0) 44 4209 6000 Fax: +91 (0) 44 4209 6060 Copyright 2018, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means,electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein is subject to change without notice. All other trademarks mentioned herein are the property of their respective owners.