Democratizing Data Science

Watched this presentation yesterday. Nicely done, non-technical overview of 'democratizing'.

Breaking Analytic Barriers: How To “Democratize” Data Science In Your Organization

Listen in to IIA’s CAO Bill Franks alongside Nick Jewell and Liam Yu of Alteryx for this webinar as they share the strategies you need to implement to optimize the value of your analytic workforce and increase the leverage of data science within your organization. They will talk through key areas that can quickly drive change and help you understand some of the pitfalls to avoid. In this webinar they will cover:

● How can democratizing data science drive business value?

● What does this look like in practice?

● How do you identify advanced analytic opportunities and requirements for different stakeholders? ... 

(Requires registration)

International Institute of Analytics

Brought back to my attention, the IIA, International Institute of Analytics

See also:

Bill Franks
Analytics & big data focused speaker, blogger, consultant, and author.   Chief Analytics Officer for The International Institute For Analytics (IIA), where he provides perspective on trends in the analytics and big data space and helps clients understand how IIA can support their efforts to improve analytic performance. In his role, he helps guide IIA’s global community of analytics practitioners in determining the best strategy and path forward for their particular analytics journey.  .... 

IIA is the authority on analytics maturity and best practices.

Founded in 2010 by Jack Phillips and Thomas H. Davenport, the International Institute for Analytics is an independent research firm that works with organizations to build strong and competitive analytics programs.

IIA offers unbiased advice in an industry dominated by hardware and software vendors, consultants and system integrators. With a vast network of analytics experts, academics and leaders at successful companies, we guide our clients as they build and grow successful analytics programs.

Since its inception, IIA has worked with more than 200 organizations, sharing the keys to analytics maturity so that our clients gain an edge in an economy increasingly driven by data. Through our in-depth research library, moderated phone calls, webinars and events, our clients get the guidance and expertise needed to compete on analytics and win. ... " 

Analyzing the Internet of Things

Teradata's Bill Franks on the IOT.   Nice concise thoughts.  Like Big Data, the IOT's engine is analytics and then translating that to decison.  Not sure we need another acronymn (AoT), but I accept it as a reminder of the fundamental need for value from data.

" .... To date, a lot of effort has been put into creating sensors, deploying them, and generating masses of data. However, lagging behind that effort is the analysis of the data. As with any data, no value is driven without analysis and action. It would have been better if more thought was given to how to utilize the data generated prior to creating sensors that stream it out. Given that we are where we are, the best path forward is to begin to aggressively analyze the data of the IoT. This is what I, and others, have begun to call the Analytics of Things (AoT). ... "

Netflix, Analytics and What You Watch

In FutureStartup: Correspondent Bill Franks chief scientist at Teradata, talks about his analytics experiences with Netflix.    Further thoughts: " ... Teradata’s Franks said that if it wanted to, Netflix could almost be a stand-alone analytics firm.  ... “It is getting blurry out there as to what companies are in,” said Franks. “AT&T is not just a phone provider. It is providing TV, and then has its own data. Nike is now manufacturing high-tech electronics and housing data in its data center, not just doing knitted sportswear. Companies can commercialize the use of their data outside of their core business. It is a fascinating time, and a lot of companies will be morphing and twisting.” ... " 

Discovery Analytics

Bill Franks of Teradata on Discovery analytics.  We used to call it  exploratory analytics, and every project started with some of that.  Which is why data visualization was so useful, even before we had so many tool options.   Good thoughts, he writes:  "  ...  I spend a lot of time these days talking with companies about the need for a formal approach to enabling what is often called “discovery analytics” or “exploratory analytics.” What I find is that many people have a fundamental misunderstanding of what discvery analytics is all about. There is one analogy that I have found to be effective in getting people to better understand the concept. In this blog, I’ll walk you through that analogy.  ... "      I agree.   Worth reading his complete argument.

How does this differ from the Watson Discovery Advisor, which I have written about before?  See the Watson Discovery Advisor tag.   The Discovery Advisor is more knowledge management than analytics oriented.  But it would make sense to combine the two for many applications.

Informs Conference on Business of Big Data

I see that Bill Franks of Teradata will be the keynote speaker at the Informs conference on The Business of Big Data.  San Jose, June 22-24.  " ... Putting Big Data to Work ... At Teradata and throughout his career, Bill Franks has focused on translating complex analytics into terms that business users can understand and then helping organizations implement the results effectively within their processes.  ... "   More details here.  I wrote about Bill Franks excellent book on the subject here previously: Taming the Big Data Tidal Wave.  I like the elements of data concepts, Big Data and business analytics being combined in the conference.  Hope to attend.  More information here as the date approaches.  More information about Bill Franks in this blog.

Perfect Data and Perfect Predictions

An obvious conclusion: you never get perfect answers.  Analytics depends upon the correctness if the data in context, AND the power of the model being used.  Bill Franks covers some of the landscape:  

" ... Many organizations attempt to achieve “data nirvana” by having 100% complete information for any given business decision. In the customer analytics space, this is sometimes referred to as a “360 degree view of the customer.” However, we really never know everything about our customers. What we call a 360 degree view is really just the most complete view we have at any given time. All of the information we are missing must be inferred or assumed through analytics. The more complete our picture, the less we have to infer, but realistically we are usually inferring far more information than what we have in our possession. ... " 


I further suggest that your success from the value of the results you get is dependent on what you do with the always somewhat incorrect results that you get from the model.   This often depends on how the results are integrated with the decision model. I point again to my simple decision circle model.  Its
not a 360 degree view, its how it all fits together.

Teradata Blogs

Recently had cause to take a look at Teradata.  I revisited their set of blogs, which cover database, big data and analytics topics.  Paying good attention to innovation areass.   Included is a blog by Bill Franks, whose book I have mentioned here earlier.   Have added the set of blogs to my feed.  Expect to hear more from that direction.

Books on Big Data Science

Recently sent out to a requesting correspondent, in particular emphasizing the business analytics aspects:

A very readable, up to date book:  Big Data: A Revolution that will transform ...  by Viktor Mayer-Schonberger  and Kenneth Cukier...   This book answers the question WHY, with lots of recent examples ...

   And a more HOW book, in a number of interesting target areas:  Modeling Techniques in Predictive Analytics, By Thomas W Miller    Examples in the R language.

Also the Bill Franks book I mentioned earlier is also excellent:  http://eponymouspickle.blogspot.com/2012/05/taming-big-data-wave.html

But I now recommend the top two first.

I cover these, review and link them and many other books in my excerpt here:
     http://eponymouspickle.blogspot.com/search/label/books

I talk big data as well:
     http://eponymouspickle.blogspot.com/search/label/Big%20Data

Be glad to talk any and all of this in detail.
   

Sensors as Teenagers

In the Cisco Blog:  An excellent piece by Bill Franks of Teradata.  See his book I reviewed here: Taming the Big Data Tidal Wave.  About the Internet of the things and how it will operate, and about the information it will generate.   Some excellent points, good read.  " ... The primary issue for you to consider isn’t the way that our things will communicate directly to us the important facts they find. Rather, it is how they will communicate to each other as they identify those important facts. The connected things may very well end up being much more like a gaggle of teenagers than anything else. By that, I mean that they may chatter on incessantly about topics that few others find remotely interesting or important. Just as we grownups filter out the giggling teens at the mall, we will also have to filter out much of the chatter generated by our things. ... " 

Unified Environments for Big Data Analytics

A good piece by correspondent Bill Franks, whose book on the topic I previously reviewed.  It addresses some problems I am addressing in a project design  now.

" ... It is challenging to make big data simple to access and easy to analyze. While there are many reasons for this, the one I want to focus on here is that handling big data, given how big data projects are usually implemented today, requires users to learn new tools and technologies. This makes adoption a difficult and lengthy journey. ... We are reaching a crossroads in the world of analytics. Over the years, we have seen analytic environments and data environments begin to merge through the advent of in-database processing within relational database engines. This trend had been leading to a world where analytic professionals don’t have to worry about moving data or accessing different systems to perform analytics. They could simply run their analytic processes against the data where it sits using the tools they know best.  Scale could be added to analytic processes even while also simplifying them and using less system resources. ... " 

An Easy Button for Big Data?

Bill Franks, who has an excellent book out on big data analytics, writes about the lack of an 'easy button' for big data.  Insightful thoughts.  " ... It is good to remember in today’s hype-filled big data world that there is no “easy” button for big data. In fact, in many ways, big data is quite difficult to deal with. Many organizations seem to be falling for the fallacy that simply implementing new tools or platforms will “automagically” solve their big data problems. Unfortunately this isn’t the case.... For example, there is a common belief that MapReduce platforms such as Teradata Aster or Hadoop can tame big data in and of themselves.  In reality they don’t inherently enable new functionality or analytic logic to be executed. Rather, they allow you to scale certain kinds of functionality and analytic logic in a way that makes the functionality and logic much more powerful and widely applicable.... " 

Taming the Big Data Wave

I have been reading: Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics  by Bill Franks.  

I read this in preparation for several invited talks about the intersection of Big Data, visualization and analytics.  This is an excellent, largely non-technical view of this exploding area.   In particular I like how it addresses the integration of analytical expertise to businesses.  That advice can be used whether your data is 'big'  or not.  Also intriguing was his description of an 'analytics innovation center' and how teams can be used to staff and empower this idea.  Good thoughts there .... we implemented aspects of this in the enterprise, where the centers were set up to address particular kinds of data for functional parts of our enterprise.  That was done because the ready access to specific data sources and subject matter expertise was key to making the idea work

This book is a great introduction to the subject.  Managers should read it.  All technology areas like this exist on quickly shifting ground ... but this is a case where the analytics part is not shifting as quickly, and can often be used in a plug-and-play way to address  business process improvement.  So this will be useful for a long time to come, when integrated with other online and vendor resources that keep you up to date.  Also many and varied industry examples.   I will follow up with more points of view from this book.

What is in-Memory Analytics?

Bill Franks provides a good overview.    Read the whole piece, well put.  " There’s been a lot of noise lately about the concept of in-memory analytics.  As a recent example, if you followed the press around some major conferences in late April, you’ll notice that a lot of messaging was present around in-memory analytics products.  Many people have been asking questions about how in-memory can fit into their mix and how it relates to other options like in-database analytics.  So, what’s up with in-memory analytics? .... "

It is about volume, speed and complexity.  And with increasing data availability, we need more power to transform data into business value.

International Institute for Analytics

Bill Franks has a number of interesting posts at the International Institute for Analytics blog.  Like a recent post on in-memory analytics.  " ...  At IIA, we study how leading enterprises use analytics to dominate their industries. This focus allows us to go deeper than other multi-disciplined research firms. We are the market leader in benchmarking analytical capabilities and we specialize in supporting executive leadership by industry and function.... "