Big data introduction - Big Data from a Consulting perspective - Sogeti

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Big Data A start

description

Big data introduction - Sogeti - Consulting Services - Business Technology - 20130628 v5 This is a small introduction to the topic Big Data and a small vision on how to enable a (big) company in using big data and embed it into the organisation.

Transcript of Big data introduction - Big Data from a Consulting perspective - Sogeti

Page 1: Big data introduction - Big Data from a Consulting perspective - Sogeti

Big DataA start

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Big Data from a Consulting perspectiveEdzo BotjesBusiness Analyst, Sogeti Consulting Services

Amersfoort 2013 05 28

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Titel | Onderwerp | Plaats | Datum |

DATA is the NEW OIL

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People Consulted

Big Data expertsIT

Data ExpertsBusiness

InformationArchitects

Big Data expertsBusiness

Data Experts Information

Management

ArchitectsBusiness

Big Data expertsVINT

Big Data expertR20

Desk Research

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What were the questions fromThe management team?

Content

Conclusion / Answers

Actions to take as MT

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What were the questions

• Question 1 - What is Big Data?

• Question 2 - Big Data in current organization?

• Question 3 - What is the future role of the Information Management department in the subject Big Data?

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Content

Conclusion / Answers

Actions to take as MT

What were the questions fromThe management team?

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Why Big Data is a MT subject

Source: http://www.myforrester.net/big-data-webinar ; http://www.airlineleader.com/pdfs/Airline%20Leader%20Issue%2014.pdf

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Why Big Data is a MT subject

Source: https://www.bmelv.de/SharedDocs/Downloads/Verbraucherschutz/Internet-Telekommunikation/SaferInternetDay2013Ksker.pdf?__blob=publicationFile page 14“Big Data, was ist das?", Dr. Holger Kisker, VP and Research Director Forrester. February 2013

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What is data / information ?

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From data to wisdom

Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 6"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem. et al. June 2012

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Role of insight

Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 8"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem. et al. June 2012Source: http://cci.uncc.edu/sites/cci.uncc.edu/files/media/pdf_files/MIT-SMR-IBM-Analytics-The-New-Path-to-Value-Fall-2010.pdf page 4"Analytics: The new path to Value" by IBM and MIT

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Definition of Big Data ?

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The Attack of the exponentials

Source: http://www.slideshare.net/medriscoll/driscoll-strata-buildingdatastartups25may2011clean slide 4"Building Data Start-ups: Fast, Big and Focused" by Michael E. Driscoll CTO Metamarkets, May 2011

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3 V’s that define Big Data (or 4?)

VALUE

Source: http://www.slideshare.net/multiscope/data-pioneers-sander-duivestein-vint-future-of-data slide 9“The future of data” by Sander Duivestein , June 2012

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Big Data definition at Goldman Sachs et al.

BIG DATA ==

Transaction+

Interaction+

Observation

Source: http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/"7 Key Drivers for the Big Data Market" by Shaun Connolly at the Goldman Sachs Cloud Conference May 2012

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Big Data Definition by Edzo

BIG DATA ==

Real time data+

Real time analysis(graph data)

+Real time reaction

(feedback loop)

Source: Edzo Botjes

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Examples of the 3 V's

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Examples of Size and Source

Source: http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf

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Examples of Big Data Analytics

Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al.. June 2012

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Examples Big Data

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Examples of Big Data in the real life

Source:http://www.computerworld.com/s/article/9233587/Barack_Obama_39_s_Big_Data_won_the_US_election http://www.infoworld.com/d/big-data/the-real-story-of-how-big-data-analytics-helped-obama-win-212862 http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/ http://commons.wikimedia.org/wiki/File:Target_logo.svg http://www.rfgen.com/blog/bid/285148/Tesco-Improves-Supply-Chain-with-Big-Data-Automated-Data-Collection http://www.computerweekly.com/news/2240184482/Tesco-uses-big-data-to-cut-cooling-costs-by-up-to-20m http://img.dooyoo.co.uk/GB_EN/orig/0/7/7/7/3/777389.jpg

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Big Data ready?

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Your Big Data profile: what does that look like?

Big Data is concerned with exceptionally large, often widespread bundles of semi structured or unstructured data. In addition, they are often incomplete and not readily accessible.

“Exceptionally large” means the following, measured against theextreme boundaries of current standard it and relational databases: petabytes of data or more, millions of people or more, billions of records or more, and a complex combination of all these.

With fewer data and greater complexity, you will encounter a serious Big Data challenge, certainly if your tools, knowledge and expertise are not fully up to date. Moreover, if this is the case, you are not prepared for future data developments. Semi-structured or unstructured means that the connections between data elements are not clear, and probabilities will have to be determined.

Further to read:B. Ten Big Data management challenges: what are your issues?C. Five requirements for your Big Data project: are you ready?

Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al. June 2012

Are you Big

Data ready?

Or to big a

leap?

“Big”

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Most important Tip (s)

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Tips

• Never, Ever, start without a Business Case and thus a business sponsor.

• Added value of Big Data is combination of “External” Sources. Think outside the box, outside your silo.

• Maturity is key. - Start with identifying - then go optimizing, scale to BI, BI++ and - then to real time added value Big Data feedback loops

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Maturity (Big Data is young and quick)

The notion that opportunities to capitalize on Big Data are simply lying there, ready to be seized, is echoing everywhere. In 2011, the McKinsey Global Institute called Big Data “the next frontier for innovation, competition, and productivity” and the Economist Intelligence Unit spoke unequivocally of “a game-changing asset.” These are quotes taken from titles of two directive reports on Big Data, a topical theme that is developing vigorously, and about which the last word has certainly not been uttered.

McKinsey states it very explicitly:This research by no means represents the final word on big data; instead, we see it as a beginning. We fully anticipate that this is a story that will continue to evolve as technologies and techniques using big data develop and data, their uses, and their economic benefits grow (alongside associated challenges and risks).

•“Innovation”

•“Competition”

•“Productivity”

Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al. June 2012

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What were the questions

• Question 1 - What is Big Data?

• Question 2 - Big Data in current organization?

• Question 3 - What is the future role of the Information Management department in the subject Big Data?

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Big data in current organization

CRM

Internal R&DInternal BI

Social Media

Data Virtualization

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What were the questions

• Question 1 - What is Big Data?

• Question 2 - Big Data in current organization?

• Question 3 - What is the future role of the Information Management department in the subject Big Data?

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Vision / Role

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Information Management Role

be an advising guide

Bring together

Create innovation environment

Bring success to production

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Information Management Role

Facilitate Execute

Be a leader

Bring together

Create innovation environment

Bring success to production

Source: http://www.alfredoartist.com/Optimized%20Images/Rodriguez-InSearchOfGold.jpghttp://resources1.news.com.au/images/2011/07/27/1226102/848013-gold-prospecting.jpghttp://www.refinedinvestments.com/wp-content/uploads/2012/10/gold-mining400x282.jpghttp://en.rockscrusher.com/wp-content/uploads/2011/04/gold-mining-plant.jpg

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Information Management Role

Not the Information Management Role

1.Employ Data scientists2.Develop new data analyses technique’s3.Be a business sponsor

Information Management Role1.Facilitate the gold finding process (POCs)

Bring data scientist in touch with business2.Be owner of the gold mining process (projects)3.Have and Execute a vision on data governance and data virtualization. (reduce future costs on projects, POCs and changes etc.)

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What were the questions

• Question 1 - What is Big Data?

• Question 2 - Big Data in current organization?

• Question 3 - What is the future role of the Information Management division in the subject Big Data?

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Content

Conclusion / Answers

Actions to take as MT

What were the questions fromThe management team?

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Big Data Actions

Data Board

Data Governance

Data Virtualization

Create a Network

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Goals of the Data board

• Role of a Steering Committee / Governance

• Once a month (2 months) meeting

• Advice to POCs, brainstorm for POCs, Assist breaking silos, create a platform for governance issues(Possible KPI.. 3 POCs per year?)

• Great Variety inside Organization and outside (for example a professor, young people, R&D and business and more experienced internal employees)

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Subjects – Data Governance

• Where is what data ?

• Who owns the data ?

• Who owns the application that stores the data ?

• Who can access the data ?

• Who is responsible of data quality (and how) ?

• What are the legal implications and boundaries ?

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Subjects – Data Virtualization

• Future enormous cost reduction

• Improvement of MI

• Faster data centric solution

• Lower cost of projects

Source: http://res.sys-con.com/story/may11/1849158/data%20virt%20image_0.jpg

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Subjects – Create a Network

Create connections with and between:

• Universities

• External experts / stakeholders

• (Small) specialized companies

• Internal experts / stakeholders

Source: http://learnthat.com/files/2008/06/people-network1.jpg

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Content

Conclusion / Answers

Actions to take as MT

What were the questions fromThe management team?

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Big Data in the Enterprise

Data Board

Data Governance

Data Virtualization

Create a network

Facilitate Execute

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This is just the beginning