Mayo Clinic Initiative Takes Analytics to the Enterprise Level by Greg Slabodkin via @infomgmt

The Mayo Clinic's big data project is rapidly becoming one of the largest and most sophisticated analytics initiatives in the nation.

Sounds interesting to work on. The end result will be very interesting too.

SLIDESHOW: 5 Key IT Spending Trends via @infomgmt

Gartner earlier this month released its latest IT spending forecast. While overall global IT expenditures are projected to be flat this year, software was a bright spot.

Interesting looking at the items in this list with the amounts.

Artificial Intelligence Is Setting Up the Internet for a Huge Clash With Europe by Cade Metz via @WIRED

The European Union's recent General Data Protection Regulation has a clause that restricts "automated individual decision making" and provides a "right to explanation." But "automated individual decision making" is what neural networks do, and complicated machine learning algorithms defy easy explanation.

I can see the problem - it's not always so easy to explain how a decision was made.

Spurious Corrrelations by @TylerVigen

I just LOVE these and they are a great lesson to any aspiring data scientist or data analyst.

If Correlation Doesn’t Imply Causation, Then What Does? by @akelleh via Medium

Adam Kelleher’s interesting post looks at when and why you might want to use causality.

He has a second post here which discusses all about understanding bias.

Please read these at least twice as it's worth understanding these articles and the points within them well.

VIDEO: Distributed deep learning on Spark by Alexander Ulanov via @OReillyMedia

Alexander Ulanov offers an overview of tools and frameworks that have been proposed for performing deep learning on Spark.

I found this fascinating.

Business Leaders Ill-Prepared for Digital Transformation by Bob Violino via @infomgmt

Global business leaders lack confidence in their ability to successfully navigate digital transformation, according to a new study by Changepoint.

Interesting survey conclusions.

Turning Big Data into Smart Data by Gary Amos via @infomgmt

The challenge becomes - how do we bypass the overabundance of data available to make practical use of the most valuable information? The answer is smart data.

It makes sense - we have to be increasingly efficient with everything including data and our analytics.

Find Business Value in the Maturing Internet of Things by Kishore Kumar via @Data_Informed

The Internet of Things is still in its teenage years, mired in adolescence and grappling with growing pains. A recent report from Gartner said, “A recurring theme in the IoT space is the immaturity of technologies and services and of the vendors providing them.” Architecting for this immaturity poses a major challenge to businesses in every industry.

I have to agree with him.

Make a Big Impact with Big Data: 5 Lessons for Leaders by Deb Henretta, Sandy Ogg, and David Niles via @Data_Informed

Big data and advanced analytics are propelling the next wave of business transformation – endowing organisations with deep and actionable insights into customer preferences, market opportunities, and value drivers. But for many businesses, the benefits of big data have not lived up to the hype.

Interesting thoughts.

8 Business Process Analytics Every Manager Should Know by @BernardMarr via @Data_Informed

Operational analytics can help businesses increase efficiency, protect their reputations, save money, and eliminate waste. This is a broad area, covering everything from supply chain management to detecting fraud, but it is not to be overlooked. Let’s explore the key operational analytics you should be using in your business.

Great article by Bernard (as always).  There are definitely some of the 8 I haven't seen in action for real although I can definitely see why they would be valuable.

Bayesian Machine Learning, Explained by Zygmunt Zając via @kdnuggets

Want to know about Bayesian machine learning? Sure you do! Get a great introductory explanation here, as well as suggestions where to go for further study.

Very useful article with lots of links to resources.

How to Start Learning Deep Learning by Ofir Press via @kdnuggets

Want to get started learning deep learning? Sure you do! Check out this great overview, advice, and list of resources.

Great start on what to learn and how to learn it.

Demystifying machine learning by Anand Rao via PWC Emerging Technology blog

Demystifying machine learning by This is an excellent 4 post series on Machine learning by Anand.

Part 1 - Is machine learning just a fancy word…

Part 2 - Different types of machine learning.

Part 3 -Exploring Deep Learning

Part 4 - Image and Video Applications

This is an excellent series and advisable to read.

Free Alternatives to Excel for Data Cleaning by Lee Baker via @DataScienceCtrl

Pretty much every data rookie starts with Excel. It is a wonderful program for storing, cleaning and analysing (yes, you read that correctly) your data.

Very interesting.

Rescuing Retail’s Mobile Customer Experience Requires New Technology by Tony Compton via @infomgmt

For retail operators interested in the ability to quickly engage customers in the midst of any rapid change in local conditions or market dynamics, the overarching challenge has become threefold: securing a customer base that will opt in to mobile technology in advance of receiving real-time communications; employing talent that can creatively craft breakthrough notifications; and adopting a technology environment focused on making the most of opportunistic omnichannel customer experiences.

Interesting discussion.

Harnessing the Data Tipping Point of IoT by David Booth via @infomgmt

Data defines how you operate your company at a foundational level. It reflects the reality of knowing your customer to accurately fulfil orders and send invoices.

This is all about data governance which is definitely needed for IoT,

Apache Spark: The Future of Big Data Science? by Matthew Thomson via @infomgmt

Spark is different from the myriad other solutions because it allows data scientists to develop simple code to perform distributed computing.

Interesting blog.  Spark definitely seems worth learning.

What To Expect from Deep Learning in 2016 and Beyond by Sophie Curtis via @kdnuggets

This post is a collection of the opinions of many of deep learning's foremost researchers. I'll share two great nuggets here. From Andrej Karpathy of OpenAI: "We're learning what the lego blocks are, and how to wire and nest them effectively to build large castles." From Christian Szegedy of Google: "algorithms will become so efficient that they will be able to run on cheap mobile devices, even without extra hardware support or prohibitive memory overhead".

Interesting views from big players in the area.

The 4 Mistakes Most Managers Make with Analytics by Anja Lambrecht and Catherine Tucker via @HarvardBiz

There is a lot of hype surrounding data and analytics. Firms are constantly exhorted to set strategies in place to collect and analyse big data, and warned about the potential negative consequences of not doing so.

Definitely something for us all to be aware of.

We need to talk about AI and access to publicly funded data-sets by @riptari via @techcrunch

This is a thoughtful article about who should own the value that's locked up in our data.

This is really interesting and points out a few things that I never know or thought about it.

Microsoft’s Big Bang: Everything CRM and ERP On One Platform by John Bruno via @infomgmt

Microsoft is bringing together the capabilities from these products, their intelligence tools, and third party or internally-built apps from its newly launched AppSource.

Interesting.

Why a Single Customer View is Essential for Modern Marketing by Victoria Dadson via @Datafloq

The traditional customer journey has changed. With ever increasing innovations in technology, consumers now have access to an unprecedented array of channels and devices that give them control over exactly when and how they shop. As a result, influencing customer touchpoints and critical decisions along the path to purchase has become steadily more complex for businesses.​

In my experience there are several problems to that.  Duplicate customers and disconnected systems. It can be devilishly hard to have a single customer.

The land grab for farm data by @jasontatge via @TechCrunch

The rise in precision agriculture has created a massive influx of unstructured farm data, creating new opportunities in an industry that's been operating solely in the physical realm.

Interesting. Never was farming so complicated with all this data.

WEBINAR: Faster Self-Service Analytics with Salesforce Data and Visualizations - 26 July 2016

Overview

Title: Faster Self-Service Analytics with Salesforce Data and Visualizations

Date: Tuesday, July 26, 2016

Time: 09:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

Faster and Richer Self-Service Analytics with Salesforce Data and Visualizations

The de facto CRM for most organizations today is Salesforce. The sales, marketing, and service data found in Salesforce often needs to be combined with other data sources for impactful business insights.  Blending, enriching, and analyzing Salesforce data with other sources takes time and slows time to critical insights.  How can these analytic obstacles be overcome?

In this Data Science Central Webinar, you will learn how you can easily harness the power of Salesforce by using self-service analytics to:

• Blend your Salesforce data with other data sources, including databases, applications and spreadsheets – in hours, not weeks
• Apply advanced analytics to your CRM data for richer insights
• Produce dashboards and visualizations for analysis

Join us for this live webinar and see how today’s leading organizations are accelerating their analytics and visualizations for deeper insights through self-service analytics.

Speakers:

Raman Kaler, Alliance Manager -- Alteryx 
Thuy Nguyen, Solutions Engineer -- Alteryx

Hosted by: 

Bill Vorhies, Editorial Director -- Data Science Central

Register here

Why Microsoft is betting its future on AI by Casey Newton via @verge

Inside Satya Nadella’s plan to outsmart Google.

This is really interesting and points as to how some of their products are going to change.

VIDEO: EmTech Digital videos via @techreview

Lots to think about in this collection of short talks from the recent EmTech Digital conference. Talks cover AI, robotics, and intelligent startups. Most of these are 15-20 minutes and are easy to get into.

There are some really good presentations here.

Designing Dashboards for Left-and-Right Brain Thinkers by Chris Valas via @BigData_Review

Did you know that people today have an attention span of just eight seconds? That means you only have about seven seconds to get your point across before a viewer’s attention moves on.

Interesting - I've never thought of it this way.

Balancing the Demands of Big Data With Those Of Accurate Data by Mike Azevedo via @infomgmt

But what happens if you need to handle millions of these types of transactions at once? To ask it another way, what happens when the universes of high-value transactions and Big Data collide?

This is more about new databases having more mainstream functionality around transactions and integrity.

What Every Data Scientist Should Know About Floating-Point Arithmetic by Michael via @DIYBigData

This is an overview of how the limitations of floating point numbers can (and will) impact data science and other big data applications.

This is essential reading and something I've had to be careful of myself.

Don't underestimate "easy" when it comes to data access by Timothy McGovern via @OReillyMedia

The difference between failure and success may be the difference between making analytics possible and making it straightforward.

Sometimes it is harder to do something simple in a correct manner.  I know it doesn't make sense but if you aren't trying hard enough things can go wrong.

The dynamic forces shaping AI by Beau Cronin via @OReillyMedia

It’s time to debate scenarios that will shift the balance of data, compute resources, algorithms, and talent.

I found this really interesting.  I'm still thinking about it so can't share any conclusions.

Big Data Drives Price and Revenue Optimization by Robert Kugel via @infomgmt

Price and revenue optimization is used to effect demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share.

Yes it's definitely different to traditional pricing but I can see what he is getting at.

WEBINAR: 4 Steps to improve your Search Technology and Boost Sales, BI and User Experience - 19 July 2016

Overview

Title: 4 Steps to improve your Search Technology and Boost Sales, BI and User Experience

Date: Tuesday, July 19, 2016

Time: 09:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

4 Steps to improve your Search Technology and Boost Sales, BI and User Experience

Visitors who search within e-commerce sites are two to three times more likely to convert compared to those who don't.  Improving search relevancy and user experience can significantly boost your bottom line.  Frequently, users will search for a product, don’t find it, and leave because of poor search technology/algorithms.  This webinar addresses these issues.

In this latest Data Science Central Webinar event, you will learn from CrowdFlower and its customers --Adobe and Etsy-- four techniques to improve your search relevance practices, business outcomes and user experience.

• Measurement:  To update your site’s internal search functionality, it’s vital that you know exactly what metrics your company should optimize. Learn how you should sample queries for measurement.
• Incorporating Human-Labeled Data:  Labeled Data-Metrics such as click data are valuable, but on their own they don't tell the complete story. Human-curated training data can contribute valuable additional information. CrowdFlower, Adobe and Etsy will share how they use a human-in-the-loop approach to grade results, whether it involves images, descriptions, or an entire page of results.
• Improve your search filtering UI:  CrowdFlower, Adobe and Etsy will share how they examined their individual result pages to help build out additional categories and tags to improve customer search experiences. 
• Ranking features:  A key use of human-curated training data is ranking features. Adobe will discuss how they use a human-in-the-loop approach to verify their deep learning image tagger based upon contributor photographers.

Learn how these leading companies design their site search interfaces, surface their results, and constantly refine them to enhance your own site’s search relevance to improve customer experience.

Speakers:
Lukas Biewald, CEO and Co-Founder -- CrowdFlower 
Jaime DeLanghe, Product Manager -- Etsy
Andy Edmonds, Search Science Architect -- Adobe

Hosted by: 

Bill Vorhies, Editorial Director -- Data Science Central

Register here

Big Data Vendors See the Internet of Things Opportunity by Paul Miller via @infomgmt

We're moving from expensive and specialist analytics teams towards an environment in which processes, workflows, and decision-making throughout an organisation can become usefully data-driven.

I look forward to his report.  I think we can all see that IoT is the next big thing after Big Data.

How Much is that Big Data Worth? - Big Data Decisions Impact Business Valuations by Judy Selby and Melissa Kosack via @Datafloq

As both digital and more traditional companies become more and more dependent on data to compete in today’s information economy, data is starting to have an irrefutable impact on companies’ valuation and reputation. The decisions companies make about how to use data can have an enormous impact on the success of modern enterprises, as well as on their image, their public perception, their competitors, and regulators.​

I found this really interesting.  I think most of us don't consider company worth and risk to that worth as part of our use of data.

Value of Geospatial Data Applications Extends Beyond IoT by Ali Hodroj via @Data_Informed

Location data holds valuable insights for many business verticals beyond the province of the expanding Internet of Things, writes Ali Hodroj of GigaSpaces.

I can see there are many uses and interesting analytics that can be done using this data.

SLIDESHOW: Future of Big Data: 12 Society & Technology Trends to Expect by David Weldon via @infomgmt

What does the future of big data hold? NTT Data released the 4 areas of information technology trends and 8 technology trends in its report "Looking Ahead: Technology Trends Driving Business Innovation."

Interesting read.

Text Mining 101: Topic Modelling by Goutam Nair via @kdnuggets

We introduce the concept of topic modelling and explain two methods: Latent Dirichlet Allocation and TextRank. The techniques are ingenious in how they work – try them yourself.

I found this really interesting.

40 Techniques Used by Data Scientists by Vincent Granville via @DataScienceCtrl

These techniques cover most of what data scientists and related practitioners are using in their daily activities, whether they use solutions offered by a vendor, or whether they design proprietary tools. When you click on any of the 40 links below, you will find a selection of articles related to the entry in question. Most of these articles are hard to find with a Google search, so in some ways this gives you access to the hidden literature on data science, machine learning, and statistical science. Many of these articles are fundamental to understanding the technique in question, and come with further references and source code.

This is a GREAT resource and should be bookmarked so you can go back to it over and over again.  Great content at the links to.

Bad Data, Bad Data Flows Still Plague Many Firms by Bob Violino via @infomgmt

Enterprises of all sizes face challenges on a range of key data performance management issues, from stopping bad data to keeping data flows operating effectively, according to a new survey.

I've seen this myself - a lot of care and work needs to be made in any data input so that is is usable.

5 Data Management Lessons from LinkedIn Acquisition by Manish Sood via @Data_Informed

Reltio CEO Manish Sood writes that Microsoft’s acquisition of LinkedIn reveals important truths about the nature of data management.

Five Myths About Machine Learning You Need To Know Today by Amy Krishnamohan via @forbes

Ask people outmost side academia or Silicon Valley what comes to mind when they hear the term “machine learning” and you’re likely to get a response that involves a movie like “The Matrix” or “Ex Machina.” You’re less likely to hear how it’s a great tool for fraud detection or supply chain optimization, and that’s too bad.

Great article.

WEBINAR: New Methods for Data Preparation, Advanced Analytics, and Visual Analytics - 14 July 2016

Overview

Title: New Methods for Data Preparation, Advanced Analytics, and Visual Analytics

Date: Thursday, July 14, 2016

Time: 02:00 PM British Summer Time

Duration: 1 hour

Summary

New Methods for Data Preparation, Advanced Analytics, and Visual Analytics

To gain a competitive advantage, businesses need to be able to access, blend, and perform advanced analytics on all their data.  Traditionally the analytic process would involve multiple groups, the slow building of data marts and intensive coding.  However new tools allow businesses to create a culture of self-service analytics, by enabling all these steps within an easy to use repeatable workflow and ad hoc data discovery through visual analytics.  In this webinar you’ll learn by example as we walk through how to:

• Perform basic data blending tasks such as parsing XML data
• Utilise predictive analytics to analyse part failure trends
• Apply spatial analytics to find and analyse customer behaviour by store
• Output all underlying analytic work to visual format

Register for this webinar and see how you can establish an easy method for data blending, advanced analytics, and visual data discovery with Alteryx and Tableau.

Speakers:
Shaan Mistry, Solutions Engineer -- Alteryx 
Thomas Christian, Senior Product Consultant -- Tableau 

Register here

WEBINAR: Self-Service Data Onboarding - 14 July 2016

Can your business users onboard new data?

Modern data onboarding is more than just connecting or loading - it includes managing a changing array of data sources, establishing repeatable process at scale, and doing this all in a way that gives you governance and control over the process. 

Join this webinar to learn how Pentaho can help you:

• Accelerate self-service data onboarding with "metadata injection"
• Empower business users to onboard data themselves, with defined guidelines
• Bring customer and partner data onboard faster. 

Speaker: Jonathan Shafer, Sr. Customer Product Marketing Manager, Pentaho 

Register here

Real-Time Analytics: Six Steps For Fast, Precise Decision-Making By Roy Schulte via @forbes

How many decisions does your organisation make every week, every day, every hour – even right now, as you’re reading this article? Decisions range from operational (such as “which offer should we present to this customer?”) to strategic (such as “should we acquire this company?”).

Really useful steps on how to succeed at real-time analytics.

WEBINAR: Exploring 7 Kinds of Data Stories - 12 July 2016

Overview

Title: Exploring 7 Kinds of Data Stories

Date: Tuesday, July 12, 2016

Time: 09:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

Exploring 7 Kinds of Data Stories

What makes a story data-driven? It’s no secret that we’re all swimming in data. Journalists, in particular – but also businesspeople, analysts, students and more – want to tell stories with data. We know that the human brain is wired to understand data visually. Whether you’re looking at big or small data, bringing data visualizations into your work adds depth and detail to an article, report, or presentation.

In this next Data Science Central Webinar, we’ll cover seven types of data stories and how to incorporate them into your work. Whether you’re a reporter, a student, a businessperson, or anyone else, you’ll learn how to tell stronger, more compelling stories using data. You’ll be a better storyteller for it. 

Speaker: Ben Jones, Product Director -- Tableau

Hosted by: Bill Vorhies, Editorial Director -- Data Science Central

  

Register here

SLIDESHOW: Top 10 Strategic Technologies for Government in 2016 by David Weldon via @infomgmt

Spending on information technology is on the increase in the government sector this year, and that includes a significant portion toward data management and data analytics related issues. This week research firm Gartner Inc. released its report on “The Top 10 Strategic Technology Trends for Government in 2016...

Interesting to look at this list and compare it to what you organisation has as a priority.

Get the Most Value from your Data Science Team by Bill Schmarzo via @Data_Informed

How does an organisation get the most out of their data scientists? How do we alleviate the shortage of data scientists that threatens to stymie the business and societal benefits that these unique folks can bring forth?

Interesting thoughts and worth reading as it may give you some useful insights.

Take Tom Davenport’s Big Data Challenge by Thomas H. Davenport via @Data_Informed

Tom Davenport is administering a pop quiz on big data. Test your knowledge with this expert on all things analytics.

Good fun to do and see what you know. I scored 8/10 (the 2 US based questions were what I got wrong and that was because I just guessed).

How You Can Improve Customer Experience with Fast Data Analytics by @Ronald_vanLoon via @Datafloq

Fast data is basically the next step for analysis and application of large data sets (big data). With fast data, big data analytics can be applied to smaller data sets in real time to solve a number of problems for businesses across multiple industries. The goal of fast data analytics services is to mine raw data in real time and provide actionable information that businesses can use to improve their customer experience.​

It sounds fantastic, but I truly believe this is becoming increasingly possible to achieve.

Patterns Recur In Analytics Just Like In Nature by @billfranksga via @iianalytics

Patterns in nature occur everywhere and the most well-known pattern is the Fibonacci sequence. The same goes for data. Look for the pattern in your analytics and make use of what has already been done to deal with it. Much like the Fibonacci sequence appears repeatedly in nature, there are recurring patterns in data that, once recognised, can improve both our analytics and our efficiency in creating them.​

I agree completely.  If you can recognise the patterns you can start to use them to your advantage, reusing code/analytics/etc and even improving any predictive analytics or machine learning you might have around those areas.

How Unlimited Computing Power, Swarms of Sensors and Algorithms Will Rock our World by @vanrijmenam via @Datafloq

We have entered a world where accelerated change is the only constant. The speed at which technologies are currently developing is unlike any other since the existence of mankind.​ Today, the combination of unlimited computer power, swarms of sensors and smart algorithms will completely change our world. It will change how we live and it will change how you run your organisation. Are you ready for this change?

I think we all need to prepare for this new world which is coming to us all over time.

How Google is Remaking Itself as a "Machine Learning First" Company by Steven Levy via @backchnnl

If you want to build AI into every product, you better retrain your army of coders.

Sounds great.  Now if only I get into one of those training programmes......

IBM Opens Blockchain-Oriented, Bluemix Garage In NYC By Charles Babcock via @InformationWeek

This week, IBM added a seventh "garage" for developers. Big Blue is opening a BlueMix Garage in New York City that will focus on financial services, including the use of blockchain technology.

Interesting development - blockchain is definitely here to stay.

Hadoop Security Issues and Best Practices by Marry Tho via @Analyticbridge

The big data blast has given rise to a host of information technology software and tools and abilities that enable companies to manage, capture, and analyse large data sets of unstructured and structure data for result oriented insights and competitive success. But with this latest technology comes the challenge of keeping confidential information secure and private.

Great list of issues that are worth reading and checking through.

The Commercialisation of Data – Coming to a Business Near You by John Rogers via @infomgmt

Data has the potential to be repackaged and “commercialised” as an alternative revenue stream. Look at how Foursquare predicted a huge drop in Chipotle’s sales ahead of an official earnings announcement.

I do have some privacy concerns but it sounds great.

SLIDESHOW: 14 Business Impacts of a Cyberattack by David Weldon via @infomgmt

What is the true cost of a data breach? Research firm Deloitte says the toll of cyberattacks is significantly underestimated. The firm cites 14 factors that could have deep impact on your business and your bottom line.

I can't imagine it is easy to estimate the cost as it would touch almost every area of a business.

Using Embedded Analytics to Transform Your Business by Tom Cahill via @infomgmt

Self-service analytics can bring significant benefits to businesses, as it enables users of all roles and skill sets to access and analyse data. However, it’s not enough to just provide easy access to data analytics.

I have seen this and you need to provide training on not just the tools but the data and their meaning.

SLIDESHOW: Big Data Skills and Pay Trends That Have Top Impact by David Weldon via @infomgmt

Big data skills continue to be among the most rewarding investments for technologists, and most expensive to pay for to IT leaders, according to the newly released “IT Skills and Certifications Pay Index” by Foote Partners. Here are the skills and certification trends that will most impact you.

Maybe this can help you to know the skills and certifications to concentrate on.