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Big Data Testing We get you past the bottlenecks! TM BIG DATA

Big Data Testing · AUTOMATION MOBILE CLOUD LEGACY QA CENTER OF EXCELLENCE FUNCTIONAL FDA VALIDATION SOA SERVICES PERFORMANCE SECURITY BIG DATA AGILE AUTOMATION MOBILE CLOUD LEGACY

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Page 1: Big Data Testing · AUTOMATION MOBILE CLOUD LEGACY QA CENTER OF EXCELLENCE FUNCTIONAL FDA VALIDATION SOA SERVICES PERFORMANCE SECURITY BIG DATA AGILE AUTOMATION MOBILE CLOUD LEGACY

Big Data Testing

We get you past the bottlenecks!TM

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

Page 2: Big Data Testing · AUTOMATION MOBILE CLOUD LEGACY QA CENTER OF EXCELLENCE FUNCTIONAL FDA VALIDATION SOA SERVICES PERFORMANCE SECURITY BIG DATA AGILE AUTOMATION MOBILE CLOUD LEGACY

solutions.pyramidci.com 2

Big Data Testing

Overview

Big data is a fast-growing marketplace that is driving demand for

specialized products. These products, in turn, require specialized

testing. Pyramid helps implement testing of massively scalable

solutions for big data infrastructures. Our QA designers bring

innovative new testing solutions to performance, security, and data

quality that provide fast feedback within development iterations.

What is Big Data?

Big data is large-volume unstructured and semi-structured data that

cannot be handled by standard database management systems like

DBMS, RDBMS, or ORDBMS. The components of big data can be

described as Volume, Variety and Velocity.

Velocity: Data moves extremely fast through various sources such as

online systems, sensors, social media, web clickstream capture, and

other channels.

Variety: Data comes from many sources; structured and

semi-structured, as well as unstructured (emails, text

messages, documents, etc.).

Volume: Data size may (but not always) be in the

terabytes to petabytes (and beyond).

Challenges in Big Data testing

Scale: Big data should be quickly and flexibly scalable.

Performance: Big data must move at extremely high

velocities, regardless of scale or database workloads.

Continuous Availability: Big data systems must be

“on” at all times.

Data Diversity: Big data schemas must accommodate a variety of

configurations.

Data Security: Credit card data, personal ID, other secure information

sensitive assets must be secure at all times.

QA Infrastructure: Complex QA infrastructures must be carefully

tailored.

Pyramid Big Data Testing Solutions

Pyramid’s robust Big Data Testing Solutions (BTDS) are built to

mitigate rapidly evolving data integrity challenges and ensure robust

quality assurance processes for big data implementations. To

address dynamic changes in big data ecosystems, Pyramid helps

organizations streamline their processes for data warehouse testing,

performance testing, and test data management.

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

> Performance Testing

> Load Test

> Velocity Testing

> Failover Testing

> Security Testing

> Testing Environment and

Infrastructure Testing

> Best Practices.

> Test Automation

> Test Management

> Compliance with Industry Standards.

> Data Integration Testing

> Extract, Transform, Load

and Quality Testing

> Data Repository Testing

> Analytic Layer Testing

> Reports Validation

> Pre-Hadoop Validation

> Map Reduce Validation

> Source Verification

> Data Warehouse Testing

FUNCTIONAL TESTING

TEST DATA TESTING TOOLS

PYRAMID BIG DATA TESTING SOLUTIONS (BDTS)

NON-FUNCTIONAL TESTING

OTHER SOLUTIONS

BIG DATATESTING

Page 3: Big Data Testing · AUTOMATION MOBILE CLOUD LEGACY QA CENTER OF EXCELLENCE FUNCTIONAL FDA VALIDATION SOA SERVICES PERFORMANCE SECURITY BIG DATA AGILE AUTOMATION MOBILE CLOUD LEGACY

solutions.pyramidci.com 3

Pyramid Advantages

• Big data warehouses are organized into smaller units that are easily

testable, improving test coverage and optimizing big data test sets.

• QA designers perform parallel testing in a distributed environment.

• Test data quality is strengthened by thorough planning, designing,

and infrastructure setup process.

• Big data testing infrastructure requirements are assessed first, then

the infrastructure is designed and implemented.

• QA designer skills include white box testing and data analysis.

• More data is tested faster, using automated testing processes across

various platforms.

• Best-in-class big data testing solutions and strategies deliver more

business value.

• Pyramid brings deep testing experience across platforms, including

Hadoop, MongoDB, Oracle, Teradata, IBM, Microsoft, HortonWorks,

and all of the major vendors, along with flat files and XML.

Pyramid Big Data Testing Approach

Pyramid’s collaborative data testing solution finds bad data and provides a

holistic view of the “health” of a company’s data, ensuring that data extracted

from sources remains intact at the target by analyzing and quickly pinpointing

differences at every touch point.

Big Data Testing

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

QA CENTER OFEXCELLENCE SOA SERVICESFDA VALIDATIONFUNCTIONAL

PERFORMANCE AGILEBIG DATASECURITY

AUTOMATION LEGACYCLOUDMOBILE

FUNCTIONAL

Pyramid Consulting Inc. - World Headquarters

11100 Atlantis Place, Alpharetta, GA 30022

Phone: 678.514.3500, Toll Free: 877.248.0024

[email protected]

PYRAMID’S COLLABORATIVE

DATA TESTING SOLUTION FINDS

BAD DATA AND PROVIDES A

HOLISTIC VIEW OF THE “HEALTH” OF A

COMPANY’S DATA

LOAD SOURCE

PERFORMANCE MAP REDUCE

EXTRACT OUTPUT

> Pre-Load Process

Validation

> ETL Process Validation

> Validate Input Data File

> Performance Testing

> Security Testing

> Validate Data

Requirement

> Validate Business

Logic Nodes

> Data Quality Testing

> Validate Output

Data File

> Validate Aggregation

and Consolidation

> Validate Data Integrity

> Validate Transformation

Rules

> Validate Data Accuracy

> Reports Testing

> Cube Testing

> Dashboard Testing