cognizant bigframe fast, secure legacy migration

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 machine-learning insights.

SOLUTION OVERVIEW

Cognizant BigFrame — Solution Overview | 2

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 cost-

effectively to stay competitive in their industry.

Figure 1. Why Cognizant BigFrame

SOLUTION OVERVIEW

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.

WHY MIGRATE WHY BIGFRAME

• 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

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-marketMulti-threaded parallel execution with throttling

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.

SOLUTION OVERVIEW


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.

3Cognizant BigFrame — Solution Overview |

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.

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, sched-

ule 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 flex-

ible 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 defi-

nition language and schema.

This migration is saving the com-

pany $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-ser-

vice 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.

SOLUTION OVERVIEW

SOLUTION OVERVIEW

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 busi-

ness-changing analytics with automated

validation of the migrated data and an opti-

mized 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 busi-

ness value.

• Process Translation for Teradata Ware-

houses: BigFrame’s Translator module

automates 70 percent of the migration of

SQL statements and procedures from Tera-

data 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 Build customized solution for

each source and target

Prebuilt standard components are usable for most common

sources and targets

Support for Multiple Enterprise Data Warehouse (EDW) Sources

Create a manual process to

migrate each data source to

the required targets

Automated conversion of Teradata, Exadata, Netezza and

other data warehouses enabled through prebuilt EDW offload

module

Support for Mainframe Data Sources

Requires complex manual

conversion

Supports ASCII conversion of all mainframe data types

through our prebuilt offload module

Testing and Validation All testing requires manual

effort

BigFrame’s integrated testing engine enables automation of

40 percent of the testing process

Intuitive GUI Customer creates their own

graphical user interface to

manage and monitor the

migration

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

Teradata Process Translation

Requires complex manual

conversion

BigFrame’s Translator automates 75 percent of the migration

of components such as Teradata SQLs and BTEQs to target

platforms

Parallel Execution Only one process performed

on one file at a time

Logically related files can be grouped and transformed in a

single process

Figure 2. How BigFrame Saves Time and Money Over Manual Migration


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 tera-

bytes of data from on-premise platforms

to less expensive, faster cloud platforms

and implemented a continuous integra-

tion, continuous deployment process

(CI/CD). The continuous integration and

deployment of logical groups of data and

tables, along with the associated end-to-

end 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 pro-

viding 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.

SOLUTION OVERVIEW


SOLUTION OVERVIEW

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


https://cognizant.com/cognizant-digital-business/applied-ai-analytics/bigframe

https://cognizant.com/cognizant-digital-business/applied-ai-analytics/bigframe

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cognizant bigframe fast, secure legacy migration

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