Data Governance: 8 Key Books

Jaime Fitzgerald, New York City, June 4th 2014:

Today I helped to host and facilitate the latest half-day symposium with my colleagues on the Board of Directors of the TDWI New York Chapter.  The event's topic was "A Game-Changing Strategy for Data Management and Self-Service Business Intelligence."  The keynote by Emil Werr, Chief Architect for Data Management & Analytics at JPMorgan Chase, was on point.  The panel discussion that followed was interesting as well.

As I reflect on the day's event, my sense is that the more organizations focus on innovating and adapting to new data sources and technologies, the more they need to adapt their data governance capabilities to support these effort.  As this happens, the concept of governance extends not just to data and traditional concepts of data governance, but also to governance of processes, analytics, and decision making.  My presentation at the Data Governance in Financial Services Conference was on this topic (Governing the transformation of data into results, aka the Data to Dollars Value Chain).

With the importance of governance fresh on my mind, here are 8 recommended books on data governance.  My team and our clients find these books very helpful in approaching both the traditional data governance functions and as well as next-generation data governance challenges.  You may find these books helpful as well.

1. The Data Governance Imperative by Steve Sarsfield, a respected industry veteran like the other authors on this list.  His book is practical and readible...very helpful on a key subject, data governance, which is an important place to start.
2. The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) Print Edition -- More comprehensive than other books, this is the definitive collection of data management knowledge from the leading association dedicated to this topic (DAMA).  Also Available on CD!
3. Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) by Danette McGilvray. Practical, step by step approach to Data Quality.  Comprehensive yet Practical.  You can customize this to projects and get a lot done!
4. Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program by John Ladley
5. Big Data Governance: An Emerging Imperative by Sunil Soares.
6. Data Stewardship: An Actionable Guide to Effective Data Management and Data  by David Plotkin.
7. Master Data Management (The MK/OMG Press) by David Loshin.  Contains an excellent combination of  frameworks and practical details.  An good start to your reading on Master Data Management.
8. Data Quality: The Accuracy Dimension (The Morgan Kaufmann Series in Data Management Systems):  shorter than other data quality books, but excellent.

I hope this is helpful in your data-driven work.  Sincerely,  Jaime Fitzgerald 

TDWI NYC Panel Discussion re: Self Service BI / Data Discovery

Now live at today's TDWI NYC event is a panel discussion on Self-Service Business Intelligence featuring four speakers.  I will live blog key insights in this post, via text and embedded tweets.

Tasso Argyros Founder & Co-President. Teradata Aster:

. @targyros @tdwinyc. "used to be that data used to simply operate" but now it is a key way 2 compete #data #analytics #DataScience #TDWINYC
— Jaime Fitzgerald (@jaimefitzgerald) June 4, 2014

 Rado Kotorov, PhD Chief Innovation Officer, Information Builders:

Rado Kotorov of @infobldrs #BI adoption rates are low bc tools are too focused on #analysts and #datascientists @TDWINYC #TDWINYC
— Jaime Fitzgerald (@jaimefitzgerald) June 4, 2014

Rado Kotorov of @infobldrs #BI adoption rates are low bc tools are too focused on #analysts and #datascientists @TDWINYC #TDWINYC
— Jaime Fitzgerald (@jaimefitzgerald) June 4, 2014

 Patrick May Director of Technology, GigaSpaces:

1. Self-service data discovery and BI requires the consolidation of multiple "Analytic Models" (as well as many associated data models, platforms, standards, and technologies).  This adds complexity needs to be managed
2. This is different from traditional data warehousing bc of the speed and flexibility required
3. "The 360 degree view of the customer is still mythical, but you don't need to get 100% there to benefit from a more complete view"

 Michael Kravec Leader, Enterprise Consulting, Tableau:

1. Think long term by thinking short term (short wins and experimentation leading to longer term progress)
2. See through the false choice
3. Bring big data down to eye level ("as time goes on, your needs will change")
4. Empower users to get bigger insights 
5. Make better data out of small data
6. Ensure that big data stays out of [big] trouble
7. Start the ball rolling

Live Blogging TDWI NYC Event:

I'm live blogging this morning from today's TDWI NYC event on Game Changing Data Management, in which Emil Werr of JP Morgan Chase is giving the keynote.  His focus is on a new the challenges--and the opportunities--of integrating new data sources (so-called Big Data such as clickstream data, voice of customer data capture, massive transaction data, real-time feeds, etc.).

Emil speaks fast so I'll have to type fast too:

1. On Giving Users Earlier Access to Data While Avoiding Risk of Misuse:  "let users have access to data, and let them create new analysis of that data, but require technical review before the analysis is used" 
2. Resource Monitoring and Usage Orchestration becomes especially important a data discovery environment
3. Know When you NEED 360 Degree customer information vs. other use cases that don't.  Examples:
1. ATM Transactions Don't Require 360-Degree Customer Information
2. Customer Revenue Management Analytics Does benefit from broader customer knowledge  
4. On Governance of Data Discovery Environments and Processes:

#tdwinyc part of governance: all requests for data come through a broker. All requests are tracked.
— ScottDEpter (@septer) June 4, 2014 

5. On the Data Lab / Sandbox:

Analytic sandbox management. Need type of data and include it in analytic architecture in new ecosystem. @TDWINYC #TDWINYC
— TDWINYC (@TDWINYC) June 4, 2014

6. Job Design / Competencies:  These change a lot when you shift to a more self-service -oriented data discovery environment.  As you adjust, the function becomes more mature and efficient.
7. Overview of Functions required to create and maintain a Data Discovery Environment:

About the Event:

PROGRAM Description

A Game-Changing Strategy for Data Management and Self-Service Business Intelligence

The demand for “business insight through analytics” is accelerating.  Exploding data volumes, and integration and usability complexity impede timely and accurate delivery of those insights.  Aggressive technology and process innovation is required to keep pace.  Join the Chief Architect for Data Management & Analytics at JPMorgan Chase, and an illustrious panel of Technology Executives to learn how the Business Intelligence and Data Management profession plans to respond.

PRESENTERS and EXECUTIVE PANELISTS

Emil Werr - Chief Architect for Data Management & Analytics, and Managing Director at JPMorgan Chase, where he spearheads the data management and analytics transformation program, driving innovation and self-service analytics.  Emil has multiple patents pending in data integration and workflow, and has received several awards in technology innovation, and agile information delivery. 

Executive Panelist	Role	Technology Supplier
Tasso Argyros	Founder & Co-President	Teradata Aster
Rado Kotorov, PhD	Chief Innovation Officer	Information Builders
Michael Kravec	Leader, Enterprise Consulting	Tableau Software
Patrick May	Director of Technology	GigaSpaces

Customer Profitability Analysis: Recommended Reading

"Six Steps to Customer Profitability Analysis." Accounting Web
"How Banks Use Profitability Analysis." by Arthur Middleton Hughes, Database Marketing Institute
"Customer Profitability Measurement and Management." by Robert Kaplan, Harvard Business School
The Implementation of Customer Profitability Analysis: A case study" by Erik M. van Raaij, Maarten J.A. Vernooijb and Sander van Triestc

1. 
   
2. And finally, an article that focuses on the "conundrum" (i.e. the mixture of promise and challenge) posed by the measurement and management of customer profitability and customer lifetime value

The Customer Profitability Conundrum:  When to Love 'Em or Leave 'Em

Fitzgerald Analytics a Consulting Magazine “Best Small Firm to Work for” for 4th Consecutive Year

Fitzgerald Analytics is a Consulting Magazine “Best Small Firm to Work for” for 4^th Consecutive Year

(See last year’s article, "Best Small Firm to Work For: For the 3rd Consecutive Year, Fitzgerald Named by Consulting Magazine")

Earlier this month, Fitzgerald Analytics was honored with Consulting Magazine’s distinction of “Best Small Firms to Work for” for the 4^th consecutive year, the firm’s 2^nd consecutive year ranking #2 on the list. Since 2010 the firm has risen 13 places.

This year Fitzgerald ranked highest in Client Engagement and Work / Life Balance, ranking first overall in Work / Life Balance.

Text of the original article from Consulting Magazine below:

“For a firm like Fitzgerald Analytics, numbers matter. For the firm, the key numbers are four, two and 100. Four, as in the number of years in a row the firm has been one of our Best Small Firms to Work For; two, as both the firm’s ranking and the number of years it’s held that position in the rankings; and 100, as in the firm’s 100 percent client loyalty rate, according to Jaime Fitzgerald, the Founder & Managing Partner of Fitzgerald Analytics.

“Our long-term relationships with clients give our people the ability to see the concrete benefits of our work, which is a major driver of satisfaction,” Fitzgerald says. “We believe clients have the right to know exactly how we reach our conclusions and recommendations, and to reuse our methodologies themselves.”

That, and delivering results, he says, helps lead to those client satisfaction and loyalty rates. “The numbers don’t lie,” he says. “Clients have witnessed results that are both convincing and quantifiable.”

And, clients have the opportunity to get to know each consultant in both a professional and personal capacity, Fitzgerald says, enhancing the client experience and building a relationship of trust and understanding. It’s no surprise then, that the firm finished near the top in the Client Engagement category.

But that’s not the whole story. Fitzgerald finished first in the Work/ Life Balance category. “We have a laser focus on efficiency and effectiveness and this is what allows for work/life balance,” Fitzgerald says. “And leadership supports passions and projects outside of the office.”

“Our long-term relationships with clients give our people the ability to see the concrete benefits of our work, which is a major driver of satisfaction.”

Those “outside the office” examples include attending cultural events as an office, such as team events at the UN Foundation, the State Department’s Office of eDiplomacy, to name just a few.

But the firm’s impact outside the office doesn’t stop there. Fitzgerald has a commitment to helping the social sector with what it calls its “Data to Dollars” and “Analytics Democratized” initiatives, the goal of which is to help a broader range of firms, non-profits, and individuals to benefit from analytic best practices. In fact, Fitzgerald is publishing a book later this year called: The Data to Dollars Value Chain: A Practical Guide to Successful Analytics Projects.

This year, the firm completed a project with a national educational non-profit, Common Cents, helping them value the intangible benefit of their Penny Harvest program. “The project turned out to be an incredibly rewarding engagement for all employees and we have continued to maintain close contact with Common Cents beyond the conclusion of the project,” Fitzgerald says.

As far as the firm’s continued success as one of the Best Small Firms to Work For, Fitzgerald says: “This recognition reinforces our motivation to keep building a different kind of consulting firm.”

Jaime Fitzgerald, the Founder & Managing Partner of Fitzgerald Analytics, says: “Unlike many consultancies, we place great emphasis on humility and “listening posture” with clients. Despite the technical nature of our work, we don’t hire staff unless they display excellent listening skills, “social IQ,” and ability to empathize with others. And we reinforce these attributes in our training, mentoring, staff evaluation, and compensation incentives.”

Big Data Meets the Cloud (Post 2 of 5)

Big Data Meets the Cloud: Takeaways Pt 2 
(see the first article in the series, Big Data Explosion in the Cloud)

Imagine you are a marketing executive at a large retailer. How do you know who to target, when to target them, and what products they want to buy? Now imagine you know everything each customer has purchased, when they purchased it and even have a solid understanding of why. You have millions and millions of data points profiling your customers, giving you the opportunity to individually target each one – you could send the recent graduate a coupon for hampers, the new mom an e-mail about baby food.

Sounds good, and it’s possible with today’s technology, data and analytic innovation, but getting to this enviable potential requires navigation of numerous options (to use cloud or not? What platform? Data? Methods?). With so much information available, what do you do first? How do you turn this data into an actionable solution, and what are the tools you need to do it?

By Carmen Augustine -- August 12, 2013

Big Data itself is a relatively new phenomenon – the term has become synonymous with the recent explosion in the size, diversity and spread of both creation and processing of available data – which often requires new approaches to data storage and processing. Now that technology has been developed to take advantage of big data in cloud architecture platforms, the question is: how do we make use of what we’ve built? Who can benefit, and to what degree does the cloud democratize big data?

In last week’s article, The Big Data Explosion Meets the Cloud, I introduced the growing role of Big Data in the business world and how cloud computing platforms have changed the shape of the industry. This week, I’ll take a deeper dive into trends in the industry, innovations on the horizon and opportunities for improvement. Read on to discover the insights I absorbed from the front row of the New York Technology Council’s June 26^th live panel event “The Big Data Explosion: How to Process, Analyze and Visualize in the Cloud”!

• Scott Rose of Think Big was an advocate of using big data to cultivate more innovation and increase the focus of teams on innovative work, as opposed to day-to-day work keeping the lights on:
• “[Benefit] is only limited by the imagination of the organization…I’d be hard pressed to look at an organization in any industry that can’t benefit.”
• Mr. Rose added that in practice about 80-90% of information management budgets go towards ETL while only 10% go toward innovation – a ratio that should be flipped.
• Stuart Sim of PlaceIQ agreed that big data infrastructure has opened the door to creative business model restructuring, but cautioned that with big data comes big data processing:
• Imagine an advertising campaign that can take real time consumer data and spit out a custom-tailored advertisement.
• Though he has experienced the incredible power of real time data collection, he was quick to note that it isn’t always the most effective solution, echoing Mr. Rose’s woes about implementation of big data systems.
• “The biggest challenge around big data is assembling meaningful data you can do the science on. I spend an awfully large chunk of my time making sure data is not mangled.” 
• It’s not simply a matter of collecting petabytes of consumer data – you have to know what to look for to capitalize on this data.
• Edouard Servan-Schreiber of 10gen, who had extensive experience with predictive modeling before becoming a MongoDB specialist, agreed that data cleansing is an unfortunate fact of life but agreed that despite this necessity big data is a platform for innovation:        
• “To me it's just, ‘we won't resolve this, we'll just manage how much we want to clean [the data] before we use it’.”
• “Everything is so heavy to move, when these big organizations are trying to do anything, there is an enormous amount of data processing to do what seems like a trivial thing.”
• Cleaning and sorting through data will always be a part of the equation – in some ways there’s no way around that reality
• Despite the drawbacks, it may be worth the rigorous processing – Mr. Servan-Schreiber asserted that he could use data alone to predict if someone was falling in love

When refining the incredible potential stored in big data, it’s important to think about what you need, where it comes from and what it will take to turn that data into an asset – by keeping the end goal in mind, it’s easier to go from data to dollars focusing on innovating solutions rather than wading through an ocean of data.

The Big Data Explosion Meets the Cloud - Takeaways from NY Tech Panel: Part 1 of 5

The intersection of Big Data Analytics and Cloud Computing has great potential, yet unlocking the potential of these technologies requires capabilities, frameworks, and methodologies most companies haven't yet mastered.  At a recent New York Tech Council event moderated by Jaime Fitzgerald, panelists discussed the opportunities, challenges, and themes engendered by the rise of big data cloud solutions.

I followed the discussion from the front row, live blogging highlights and recording intriguing themes. This is the 1st of 5 blog posts in which I'll share what I learned.

By Carmen Augustine -- July 26, 2013

Companies are scrambling to capitalize on the potential of Big Data, but what does it actually mean for your business? But what specifically should companies do I do with all this data, processing power, and technology? And how do the advantages and disadvantages of the cloud change the game?  Should companies be using the cloud to approach Big Data opportunities?  If so, how and under what circumstances does this make the most sense?

Jaime Fitzgerald (Founder & Managing Partner at my firm, Fitzgerald Analytics) led the panel discussion for the New York Technology Council  at the 10gen offices in New York's times square. Panelists included cloud analytics experts EdouardServan-Schreiber, Director for Solution Architecture at 10gen, Scott Rose, Client Partner at Think Big and Stuart Sim, Senior VP of Technology and Engineering at PlaceIQ, who provided a fascinating range of opinions and case studies. From budgeting for new data infrastructure to discussing how your Fitbit might be used to price health insurance, the discussion run the gamut of Big Data applications. 

Executive summary:

• Growing yet embryonic domains: Although both Big Data and Cloud Technology have been rapidly expanding in the past few years, both trends remain in the early stages of their development and adoption.  As a result, they are simultaneously "major," "immature," and fast-evolving.
• Pros, Cons, and Constraints of cloud solutions: Cloud storage has both advantages, disadvantages, and limitations. "One size doesn't fit all needs," but the flexibility, scalability, and diversity of options make cloud-based big data solutions an important option for many firms and analytic use-cases.
• Creative applications: We heard about numerous creative and new uses of big data and cloud-based big data solutions, from natural disaster detection to tailor-made advertising campaigns.
• Innovation and iteration: Although the potential of big data is significant, unlocking this potential will require significant innovation.  This innovation, in turn, will require lots of experimentation, trials, and errors... which means organizations need to build a culture in which failure is accepted, experimentation is encouraged, and agile use of big data analytics is made possible.

About the discussion:

Panelists came from a variety of backgrounds and covered a range of topics within the field...and each of them shared unique 1st hand experiences in the use of Big Data to achieve better results. From a high school math team captain to a former Scott Henson puppet builder, the participants each had different career paths and provided a unique perspective on industry trends and growth.

Big Data Analytics in the Cloud: NYTECH Panel Event Wednesday June 26th

The Big Data Explosion: How to Process, Analyze and Visualize in the Cloud

This Wednesday, June 26, Jaime Fitzgerald will be moderating a New York Technology Council panel on big data and the role of cloud storage in the big data explosion. Experts in the field including  Edouard Servan-Schreiber from 10gen, Scott Rose from Think Big and Stuart Sim from PlaceIQ will be panelists at the event, answering questions including:

·         What types of organizations will benefit from big data and in what ways?

·         What types of benefits are we talking about, in what functions, in what business models?

·         What does a cloud-based big data solution look like?

·         What do people DO with Big Data IN the cloud…?

·         Once they build cloud based big data solutions, what are companies actually doing with data specifically?

·         What are the benefits and downsides of cloud-based big data services and applications?

·         What are "hybrid" big data architectures?

·         What are the key decisions around building hybrid architectures? What design criteria are most important?

·         How do you create a strong "big data roadmap?"

·         What are the:

o    5 most value-oriented things to know about cloud based data solutions?

o    First 5 things to do to get off to a good start in taking advantage of Big Data in the Cloud?

·         Marketing professionals often say they have too much data and not enough of the new skills needed to analyze new Big Data sources. How do you fix this problem?

·         Of all the uses of Cloud Big Data technologies, what are some of the most surprising and impressive use-cases happening already?

The panel brings a diverse mix of case studies and applications. Looking forward to a stimulating conversation with our three participants!

The event will be held at the 10gen offices, 229 West 43rd Street, 5th Floor, at 6:30pm.

Click HERE to register…

Presentations from Behavioral Finance Event: How Data Visualization Impacts Financial Decisions

Presenter Gunjan Banati

The way data is presented--and how visualization is used to present it--has a profound impact on our decisions.  As this insight has moved from academia into the private sector, Financial Services firms have begun to apply these insights in fascinating ways.

On May 1st the Analytics in Financial Services group--of which Fitzgerald Analytics is the founding sponsor--curated and organized an event on this topic.  Both featured speakers are applying behavioral finance concepts, together with data visualization tools, to help improve financial decisions.

For more on the event agenda, see our pre-event blog post here.  

Slides presented by Dan Egan, head of Behavioral Finance at Betterment:

Analytics in financial services prez behavioral finance + data visualization - visualizing risk and return from Fitzgerald Analytics, Inc.

Slides presented by Gunjan Banati, Fund Research & Analytics at Royce & Associates:

How Data Visualization Impacts Financial Decisions - Event Preview

The way data is presented--and how visualization is used to present it--has a profound impact on our decisions.  As this insight has moved from academia into the private sector, Financial Services firms have begun to apply these insights in fascinating ways.

On May 1st the Analytics in Financial Services group--of which Fitzgerald Analytics is the founding sponsor--will host an event on this topic.  Both featured speakers are applying behavioral finance concepts, together with data visualization tools, to help improve financial decisions.

Our presenters will be:

• Dan Egan, Director of Behavioral Finance and Investing at Betterment.  Mr Egan was Formerly at Barclay's Wealth and Investment where he focused on using behavioral finance to help people make better financial decisions.  His presentation will focus on the impact of how we visualize risk and return.
• Gunjan Banati, Fund Research & Analytics at Royce & Associates.  Ms Banati Manages all aspects of the investment research operations including identifying, analyzing and monitoring recommended mutual funds and alternative investments.

More on both presentations, and the experts who will give them, can be found below.

Dan Egan:

1. Theme: What people invest in really is driven in part by how the various choices are presented to them.  He aims to help people make the right decision, not the knee-jerk "OMG I have to sell now!" decision which leads to selling low and then buying high later.
2. Topic: Visualizing Financial Risk and Return, focusing on the influence of presentation format on how individuals make decisions when investing. He'll review a number of different standard methods, and introduce some new forms geared towards helping consumers make the right decisions.
3. Bio: Director of Behavioral Finance and Investing at Betterment.  Formerly of Barclay's Wealth and Investment, Americas Using behavioral finance to help people make better financial decisions.
4. LinkedIn: www.linkedin.com/in/dpegan/

Gunjan Banati:

1. Theme: Using quantitative methods and visualization within her company to decide which investments to recommend. Visualizations are then used to communicate the recommendations to clients so they believe in what is being recommended.
2. Topic: The analytics of mutual fund research, meaning the methods used to evaluate mutual fund recommendations using quantitative methods combined with visualizations.
3. Bio: Gunjan Banati, Fund Research & Analytics at Royce & Associates. Ms Banati was previously at Allegheny Financial Group where she managed all aspects of the investment research operations including identifying, analyzing and monitoring recommended mutual funds and alternative investments.
4. LinkedIn: www.linkedin.com/pub/gunjan-banati/3/380/9a6

The location for this meetup has been graciously provided by the Ricoh Technology Portal.