Business in the Driver’s Seat – An Improved Model for Integration

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The Briefing Room

Business in the Driver’s Seat – An Improved Model for Integration

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Welcome

Host: Eric Kavanagh

[email protected] @eric_kavanagh


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!   Reveal the essential characteristics of enterprise software, good and bad

!   Provide a forum for detailed analysis of today’s innovative technologies

!  Give vendors a chance to explain their product to savvy analysts

!   Allow audience members to pose serious questions... and get answers!

Mission


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Topics

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INTEGRATION & DATA FLOW

October: ANALYTIC PLATFORMS

November: DISCOVERY & VISUALIZATION


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Executive Summary The Great Divide •  The IT/Biz Divide Must End •  Agile, Not Waterfall •  Iterating Must Be Easy •  Collaboration is Mandatory


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Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected] @robinbloor


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WhereScape

! WhereScape is a data warehousing software company

!   It offers WhereScape 3D, software for planning and reality-testing data warehousing and business intelligence projects; and WhereScape RED, an integrated development environment used for building, deploying and managing data warehouses and data marts.

! WhereScape RED allows developers to automate the data warehousing life cycle


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Guest: Mark Budzinski

Mark Budzinski is the President of WhereScape. In this role, Mark sees firsthand the challenges that IT organizations face and their desire to better serve the business community with agile, rapid development of data warehouses and related data driven projects. His career has spanned management positions at Intel, Sequent Computer Systems, RadiSys, and Applied Microsystems. He holds an MBA from the Univ. of Oregon, a Master’s Degree in Computer Science from the University of Southern California, a BS in Industrial Engineering from Lehigh University, and is a graduate of The Buckley School of Public Speaking.

Mark Budzinski

President

WhereScape

WhereScape Bloor Group Briefing Room

Data Integration: It Can be Fast and Agile

September 30, 2014

Let’s Talk About the Elephant in the Room

¡  IT has its hands full

¡ New data sources abound

¡  The business employs all kinds of tricks to work around IT

¡ We hide the whole mess in human capital ¡  Consultants (hand coding) ¡  Politics ¡  Excuses

WhereScape: What We Believe

The historical record that “data warehouses

take too long to build and are too hard to

change” must evolve to a paradigm whereby

IT delivers value continuously, manages

ongoing changes cost effectively, and

mitigates risk throughout

WhereScape: What We Believe

¡ Getting the data right is critically important, yet business users can seldom articulate what they want until they see it

¡  Business users/consumers of data must be served at their pace

¡  Automate as much of the process as possible

¡  Standards matter

¡ Document everything; later changes demand it

ETL Is Not The Same Thing As…

Move Data

Transform Data

Load Data From Sources including OLTP, files, Hadoop, etc.

Create Database Objects

such as Models, Views, Facts, Dimensions, Indexes

Documentation

WhereScape Value Proposition

¡ We empower IT organizations to build, deploy, and manage their data in a timeframe and manner that creates utter enthusiasm in the business community

¡  Time to results dramatically decreases - faster

¡ Costs decrease: license and human capital - cheaper

¡ Quality is higher: documentation & transparency - better

¡ Risk is mitigated: automation & methodology – with confidence

By automating development, you get more from your “data investment”

Data Warehouse Automation Software: RED

RED is an Automated Data Warehouse Development Platform That Builds Native Target Database Objects, Documents Them, And Schedules Data To Be Loaded. RED Works Well With ETL Tools, or as an ELT Solution Using Native Loaders (e.g. Teradata TPT)

Automation Use Cases

End-to-End Data Warehouse

Development Tool

Including All ETL

Complement to Enterprise ETL, Used

For Rapid/Agile Build Out of a View or Semantic Layer

Green Field

Clean Up Hand-Written

Code and Scripts

Manage Deployments

Rewrite & Recast Heterogeneous

Database Solutions

Big Data Integration

ELT 2.0

Configuration Management

Semantic Layer

Some of Our Customers

“WhereScape RED’s tight integration with the target database and built-in best practices are empowering our resource-constrained development team to tackle a large implementation that will enable us to quickly deliver value to our institution and members.”

Su Rayburn, Director of Business Intelligence Services

“Our results using WhereScape have been extremely impressive. WhereScape enabled us to design, develop, document and deploy a production-ready solution in 6-8 weeks. Using traditional data warehouse development methods would have taken us 6-8 months.

Ryan Fenner, VP, Data Solutions Architect, Union Bank

“We estimate the development lifecycle is 20-25% of what it was previously when we were hand coding.”

Dan Mosher, Director of Enterprise Data Warehousing

Summary

WhereScape’s approach with data warehouse automation yields customer results that are stunning: faster, cheaper, and more manageable


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Perceptions & Questions

Analyst: Robin Bloor

ETL or a Jumble of Pipes?

Robin Bloor, PhD

In the Era of Big Data

u  More data has become available: •  Via social media •  From public sources •  From commercial sources •  From log files •  From unstructured sources •  Through better data harvesting

u  And it is arriving faster!! u  And users expect it to be

available faster…

Data Flow – The New Reality

u  A good deal of the new data is EXTERNAL to the business

u  This means that the data warehouse is becoming LARGER AND MORE COMPLEX

u  It also means more need for DEFINING AND REFINING the data before it hits the warehouse

u  MANAGING the data flow itself has become a necessity – better to avoid ETL spaghetti

What Does Big Data Mean to the D/W?

The Data Warehouse Challenges…

u  The data flow and data warehouse architecture cannot be completely separate.

u  Data ingest is a far bigger problem than it once was

u  The data model changes far more often

u  Data warehouse construction and maintenance are more difficult and more time consuming

Data Warehouse Automation

At the moment data warehouse creation and maintenance is often a

MANUAL activity

It is becoming TOO COMPLEX to remain a manual activity

u  It is clear (to me) how RED can have a big impact in creating a new data warehouse. How can it be used if you already have a DW and simply want to improve its operation?

u  Does RED “play well with others?” Which databases/ETL products does it work with?

u  What do you see as the sweet spot for RED? What size of company/size of problem?

u  What does RED actually compete with? Are there other products that do end-to-end DW Building & Maintenance?

u  Does RED “go large?” In respect of scale, what is your largest implementation of RED by data volumes?

u  How do you complement/work with Hadoop?

u  Does RED help with data mart creation & maintenance?


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www.insideanalysis.com

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INTEGRATION & DATA FLOW

October: ANALYTIC PLATFORMS

November: DISCOVERY & VISUALIZATION


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ATTENTION!

Opening slide image courtesy of Wikimedia Commons

Business in the Driver’s Seat – An Improved Model for Integration

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Transcript of Business in the Driver’s Seat – An Improved Model for Integration