Testing Big Data: Automated ETL Testing of Hadoop with QuerySurge

50 %
50 %
Information about Testing Big Data: Automated ETL Testing of Hadoop with QuerySurge

Published on January 31, 2014

Author: RTTS

Source: slideshare.net


Are You Ready? Stepping Up To The Big Data Challenge In 2014 - Learn why Testing is pivotal to the success of your Big Data Strategy in 2014. [Slides from 1/30/14 Webinar]

According to a new report by analyst firm IDG, 70% of enterprises have either deployed or are planning to deploy big data projects and programs this year due to the increase in the amount of data they need to manage.

The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.

Learn why testing your enterprise's data is pivotal for success with big data and Hadoop. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data warehouse - all with one ETL testing tool.

Webinar Testing Big Data: Automated ETL Testing of Hadoop Laura Poggi Marketing Manager RTTS Bill Hayduk CEO/President RTTS Jeff Bocarsly, Ph.D. Chief Architect RTTS built by

Today’s Agenda • About Big Data and Hadoop • Data Warehouse refresher AGENDA Topic: Testing Big Data: Automated ETL Testing of Hadoop • Hadoop and DWH Use Case Host: RTTS Date: Thursday, January 30, 2014 Time: 1:00 pm, Eastern Standard Time (New York, GMT-05:00) • How to test Big Data Session number:630 771 732 • Demo of QuerySurge & Hadoop built by

FACTS Founded: 1996 About Primary Focus: consulting services, software Locations: New York, Atlanta, Philly, Phoenix Geographic region: North America Customer profile: Fortune 1000, > 600 clients Software: RTTS is the leading provider of software quality for critical business systems

Facebook handles 300 million photos a day and about 105 terabytes of data every 30 minutes. - TechCrunch The big data market will grow from $3.2 billion in 2010 to $32.4 billion in 2017. - Research Firm IDC 65% of…advanced analytics will have Hadoop embedded (in them) by 2015. -Gartner built by

About Big Data Big data – defined as too much volume, velocity and variety to work on normal database architectures. Size Defined as 5 petabytes or more 1 petabyte = 1,000 terabytes 1,000 terabytes = 1,000,000 gigabytes 1,000,000 gigabytes = 1,000,000,000 megabytes built by

? What is Hadoop is an open source project that develops software for scalable, distributed computing. • • is a of large data sets across clusters of computers using simple programming models. easily deals with complexities of high of data from single servers to 1,000’s of machines, each offering local computation and storage. • detects and at the application layer built by

Key Attributes of Hadoop • Redundant and reliable • Extremely powerful • Easy to program distributed apps • Runs on commodity hardware built by

Basic Hadoop Architecture MapReduce – processing part that manages the programming jobs. (a.k.a. Task Tracker) HDFS (Hadoop Distributed File System) – stores data on the machines. (a.k.a. Data Node) MapReduce (Task Tracker) HDFS (Data Node) machine built by

Basic Hadoop Architecture (continued) Cluster Add more machines for scaling – from 1 to 100 to 1,000 Job Tracker accepts jobs, assigns tasks, identifies failed machines Task Task Task Task Task Task Task Task Task Task Task Task Tracker Tracker Tracker Tracker Tracker Tracker Tracker Tracker Tracker Tracker Tracker Tracker Data Data Data Data Data Data Data Data Data Data Data Data Node Node Node Node Node Node Node Node Node Node Node Node Name Node Name Node Coordination for HDFS. Inserts and extraction are communicated through the Name Node. built by

Apache Hive Apache Hive - a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. Hive provides a mechanism to query the data using a SQL-like language called HiveQL that interacts with the HDFS files MapReduce • • • • • (Task Tracker) create insert update delete select HiveQL HiveQL HiveQL HiveQL HiveQL HDFS (Data Node) built by

Data Warehouse Review built by

about Data Warehouses… Data Warehouse • typically a relational database that is designed for query and analysis rather than for transaction processing • a place where historical data is stored for archival, analysis and security purposes. • contains either raw data or formatted data • combines data from multiple sources • • • • • • • • • Sales salaries operational data human resource data inventory data web logs Social networks Internet text and docs other built by

Data Warehousing: the ETL process ETL = Extract, Transform, Load Why ETL? Need to load the data warehouse regularly (daily/weekly) so that it can serve its purpose of facilitating business analysis. Extract - data from one or more OLTP systems and copied into the warehouse Transform – removing inconsistencies, assemble to a common format, adding missing fields, summarizing detailed data and deriving new fields to store calculated data. Load – map the data and load it into the DWH built by

Data Warehouse – the ETL process Source Data Legacy DB ETL Process Target DWH Extract CRM/ERP DB Finance DB Transform Load built by

Data Warehouse & Hadoop: A Use Case DWH Hadoop built by

DWH & Hadoop: A Use Case USE CASE*** Use Hadoop as a landing zone for big data & raw data 1) bring all raw, big data into Hadoop 2) perform some pre-processing of this data 3) determine which data goes to EDWH 4) Extract, transform and load (ETL) pertinent data into EDHW ***Source: Vijay Ramaiah, IBM product manager, datanami magazine, June 10, 2013 built by

DWH & Hadoop: A Use Case Use case data flow Source Data Source ETL Process Target DWH ETL built by

Testing Big Data built by

Testing Big Data: Entry Points Recommended functional test strategy: Test every entry point in the system (feeds, databases, internal messaging, front-end transactions). The goal: provide rapid localization of data issues between points test entry point test entry point Source Data Source Hadoop ETL Process Target DWH B I ETL built by

Testing Big Data: 3 Big Issues - we need to verify more data and to do it faster - we need to automate the testing effort - We need to be able to test across different platforms We need a testing tool! built by

About QuerySurge built by 21

What is QuerySurge? QuerySurge is the premier test tool built to automate Data Warehouse testing and the ETL Testing Process built by

What does QuerySurge ™do? QuerySurge finds bad data • Most firms test < 1% of their data • BI apps sit on top of DWHs that have at best, untested data & at worst, bad data • CEOs, CFOs, CTOs, executives rely on BI apps to make strategic decisions • Bad data will cause execs to make decisions that will cost them $millions • QuerySurge tests up to 100% of your data quickly & finds bad data built by

QuerySurge Roles & Uses Testers - functional testing - regression testing ETL Developers - unit testing Data Analysts - review, analyze data - verify mappings and failures. Operations teams - monitoring built by

QuerySurge™ Architecture Sources Target built by

QuerySurge™ Modules Design Library  Create Query Pairs (source & target queries) Scheduling  Build groups of Query Pairs  Schedule Test Runs built by 26

QuerySurge™ Modules Run Dashboard  View real-time execution  Analyze real-time results Deep-Dive Reporting  Examine and automatically email test results built by

The QuerySurge solution… verifies more data  verifies upwards of 100% of all data quickly automates the testing effort the kickoff, the tests, the comparison, emailing the results tests across different platforms any JDBC-compliant db, DWH, DMart, flat file, XML, Hadoop speeds up testing up to 1,000 times faster than manual testing built by

QuerySurge Value-Add QuerySurge provides value by either: in testing data coverage from < 1% to upwards of 100% in testing time by as much as 1,000 x combination of testing time in test coverage while in built by 29

Return on Investment (ROI)  redeployment of head count because of an increase in coverage  a savings over manual testing (minus queries, manual compares, other)  an increase in better data due to shorter / more thorough testing cycle, possibly saving $ millions by preventing key decisions made on bad data. built by 30

Demonstration Jeff Bocarsly, Ph.D. Chief Architect RTTS Ensuring Data Warehouse Quality

Add a comment

Related presentations

Presentación que realice en el Evento Nacional de Gobierno Abierto, realizado los ...

In this presentation we will describe our experience developing with a highly dyna...

Presentation to the LITA Forum 7th November 2014 Albuquerque, NM

Un recorrido por los cambios que nos generará el wearabletech en el futuro

Um paralelo entre as novidades & mercado em Wearable Computing e Tecnologias Assis...

Microsoft finally joins the smartwatch and fitness tracker game by introducing the...

Related pages

Testing Big Data - Automated ETL Testing of Hadoop ...

Automate your Hadoop testing effort to speed up testing, reduce risk & improve data quality
Read more

Testing Big Data: Automated ETL Testing of Hadoop with ...

Stepping Up To The Big Data Challenge In 2014 ... Testing Big Data: Automated ETL Testing of Hadoop with QuerySurge
Read more

Big Data Testing | QuerySurge

... in your Big Data store. Big Data testing is ... QuerySurge is the collaborative data testing ... Big Data: Automated ETL Testing of Hadoop with ...
Read more

Testing Big Data: Automated ETL Testing of Hadoop with ...

... Learn more at www.querysurge.com According to a new report by ... Testing Big Data: Automated ETL Testing of Hadoop with QuerySurge by RTTStv ...
Read more

QuerySurge: 7-Minute Demo of ETL Testing tool - YouTube

Testing Big Data: Automated ETL Testing of Hadoop with QuerySurge - Duration: ... QuerySurge - the leader in ETL testing - Duration: 3:28.
Read more

Leveraging QuerySurge for Big Data Testing - Ness Software ...

Leveraging QuerySurge for Big Data Testing 10 ... Tags: big data testing, querySurge, ... Testing Big Data – Automated ETL Testing of Hadoop with ...
Read more

ETL Testing | Informatica US

Need an automated ETL testing tool to avoid SQL scripting and eyeballing? Informatica has a ETL testing tool ... Hadoop World is where big data's ...
Read more

Big data and Hadoop Testing Training certification online ...

Enroll for Big data Hadoop Testing training and tutorial classes online. Learn Big data Hadoop Testing course to master testing skills on big data and Hadoop
Read more