Preparing Big Data for Analysis with Easyl
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This document discusses different approaches to data preparation for business intelligence. It describes manual data preparation as time-intensive and not scalable. Large IT projects can automate data preparation but require high initial costs. Technology solutions provide a middle ground by offering collaborative data preparation tools that are quicker and cheaper than large projects but require new skills. The document then discusses Progress Easyl as an example technology solution, highlighting its features like uniting different data sources, filtering and enriching data, and sharing reports.
Preparing Big Data for Analysis with Easyl
- 1. Data Preparation Made Easy Neeraj KP, Senior Software Engineer Progress Software nparakka@progress.com
- 2. © 2015 Progress Software Corporation. All rights reserved.2 About me • B.Tech from Pondicherry Engineering College, Pondicherry, India– 2010 • Software Engineer - Cordys Software (now OpenText Cordys) from 2011 – 2014 • Progress Hyderabad(2014 – Present). Part of the Easyl WebUI team. • Primarily interested in web technologies like AngularJS, Bootstrap, ExtJS etc
- 3. © 2015 Progress Software Corporation. All rights reserved.3 Business Intelligence This is what I have This is what I want
- 4. © 2015 Progress Software Corporation. All rights reserved.4
- 5. © 2015 Progress Software Corporation. All rights reserved.5 Why is this so hard? Data preparation can also involve enriching data.
- 6. © 2015 Progress Software Corporation. All rights reserved.6 How can Data Preparation Be Performed • Manual “Brute Force” Data Preparation • Data Preparation through Large IT Projects • Technology Solutions
- 7. © 2015 Progress Software Corporation. All rights reserved.7 Manual “Brute Force” Data Preparation Manual Exports Manual Joins and Filters Master List Shared via email Shared via Dropbox Limitations With This Approach • Every report starts from scratch • Each export can reset the process • Time intensive joins and filters • No governance on sharing • Reliance on other departments • Not repeatable, not scalable
- 8. © 2015 Progress Software Corporation. All rights reserved.8 Data Preparation through Large IT Projects • Large-scale IT projects can automate the handling of data before it goes into BI • Involves creating “data marts” or “data warehouses.” • Software developers and database administrators collaborate. • Extremely fast after the initial setup. • Initial setup can cost hundreds of thousands of dollars.
- 9. © 2015 Progress Software Corporation. All rights reserved.9 Data Preparation through Large IT Projects • Large-scale IT projects can automate the handling of data before it goes into BI • Involves creating “data marts” or “data warehouses.” • Software developers and database administrators collaborate. • Extremely fast after the initial setup. • Initial setup can cost hundreds of thousands of dollars.
- 10. © 2015 Progress Software Corporation. All rights reserved.10 Technology Solutions • It is in between the manual and project approach. • New generation of data preparation tools. • Quick and accurate without large investment. • Collaborative approach between data analysts line-of-business decision-makers, and systems administrators. • Data preparation tools require new skill sets and a learning curve. • Example : Easyl DataBlender
- 11. © 2015 Progress Software Corporation. All rights reserved.11 How Easyl Solves Cloud Data Mart On-premise Data OpenEdge SQL Server Big Data Union and Filter Quality and Enrich Produce View ODBC/JDBC Publish as Excel Easyl Gallery Dropbox-like report sharing Favorite Dashboard or BI Tool For You or Your Customer SaaS Data
- 12. © 2015 Progress Software Corporation. All rights reserved.12 Progress Easyl Key Features
- 13. © 2015 Progress Software Corporation. All rights reserved.13 Demo
- 14. © 2015 Progress Software Corporation. All rights reserved.14 Thank you