Why Is IoT So Insecure? by Christopher Lamb via @DZone

Taking a look at IoT, high demand for functionality and poor forethought have led to serious security breaches. But the industry can still act toward common standards.

I think like all new technology it starts with no standards, but definitely for widespread adoption IoT vendors must start thinking seriously about security.

The power of data ownership: Getting it right in 2017 by @joshmanion via @martech_today

Columnist Josh Manion believes that complete data ownership is the only option for enterprises seeking to engage individual consumers with relevant and timely experiences.

I found this really interesting - it's really important to identity the owner of data, the meaning of it, how to get it updated or changed, and how long it should be there.

Who Owns Blockchain? Goldman, BofA Amass Patents for Coming Wars by Olga Kharif via @infomgmt

Recently, some of the biggest names in business, from Goldman Sachs to Bank of America and Mastercard, have quietly patented some of the most promising blockchain technologies for themselves.

This definitely is building up to be a showdown.

Data Product to Support Research On Human Genome by Fred Bazzoli via @infomgmt

PHEMI, based in Vancouver, is releasing PHEMI Central Precision Medicine Edition to address the data challenges posed by genomic research.

This looks interesting - it's just an example of how code reuse can save time.

The Great A.I. Awakening by Gideon Lewis-Kraus via @NYTmag

How Google used artificial intelligence to transform Google Translate, one of its more popular services - and how machine learning is poised to reinvent computing itself.

This is long but SO worth the time investment to read.

Google DeepMind Makes AI Training Platform Publicly Available by @jeremyakahn via @technology

DeepMind is open-sourcing the source code for its training environment (previously called Labyrinth, now DeepMind Lab). You can download the code and customise it to help train your own artificial intelligence systems—or create new game levels for DeepMind Lab and upload these to GitHub.

Something fun to have a play with and see what you can achieve.

What You Are Too Afraid to Ask About Artificial Intelligence by @Francesco_AI via @Datafloq

Machine Learning

Artificial Intelligence is moving at a stellar speed and is probably one of most complex and present sciences. The complexity here is not meant as a level of difficulty in understanding and innovating (although of course, this is quite high), but as the degree of interrelation with other fields apparently disconnected.​ There are basically two schools of thought on how an Artificial Intelligence should be properly built

Neuroscience

Along with the advancements in pure machine learning research, we have done many steps ahead toward a greater comprehension of the brain mechanisms. Although much has still to be understood, we have nowadays a slightly better overview of the brain processes, and this might help to foster the development of an Artificial General Intelligence. So what is neuroscience and how does it relate to Artificial Intelligence?

Technologies

The recent surge of AI and it is rapidly becoming a dominant discipline are partially due to the exponential degree of technological progress we faced over the last few years. What it is interesting to point out though is that AI is deeply influencing and shaping the course of technology as well.

These are great and well worth the time investment to read through them.

EBOOK: Embedded Analytics Empower the Citizen Data Scientist via Statistica

With the advent of technologies that connect more people, machines and processes to one another, the importance of extending advanced analytics and machine learning to your users is growing fast. But the effort to derive maximum benefit from those advanced analytics is still limited in most organisations by the human element. Data scientists, seen as the only people sufficiently trained to navigate big data successfully, become the bottleneck.


Download from here

What Business Intelligence Skills Do You Need On Your Team? by Boris Evelson via @infomgmt

You have gone through the Discover and Plan of your Business Intelligence strategy and are ready to staff your support organisation. What skills, experience, expertise and qualifications should you be looking for?

Interesting suggestions.

SLIDESHOW: Top Companies for Data Quality Tools: Leaders and Challengers by David Weldon via @infomgmt

Great data analysis starts with top data quality, which is why the data quality tool market is growing at nearly 50 percent faster than the enterprise software market overall. Gartner’s latest Magic Quadrant report looks at the top vendors in the market

Interesting companies in the list.

Breaking Down Big Data Barriers in 2017 by David Gorbet via @infomgmt

Enterprises will find that it’s harder than they thought to bring together the data they want to use in their predictive models, especially unstructured data and the most important data of all: customer event data.

I would point you to the Slowly Changing Dimensions technique which is nicely described here.

The major advancements in Deep Learning in 2016 via Tryolabs Blog

Deep Learning has been the core topic in the Machine Learning community the last couple of years and 2016 was not the exception. In this article, we will go through the advancements we think have contributed the most (or have the potential) to move the field forward and how organisations and the community are making sure that these powerful technologies are going to be used in a way that is beneficial for all.

This a really good article which needs the time to read it properly (and it deserves that you do that). So set aside 10 minutes to go through it.

Found in translation by Barak Turovsky via @Google

Google has replaced its old statistical machine translation method with a new one based on deep learning.

Great example in the article which just shows what is possible.

Big Vendors Deserve Some Respect by David Menninger via @infomgmt

The fundamental problem is a mismatch in expectations. As an industry we should not generally expect groundbreaking innovations from the largest software companies.

I see what he is getting at - just not so sure others would agree with him being so understanding.

What CIOs Say About Business Intelligence and Analytics by Cindi Howson via @infomgmt

At the Symposium, I facilitated a round table discussion on how to modernise BI and analytics portfolios, presented on this year’s BI and Analytics Magic Quadrant, and conversed with more than 40 CIOs.

Interesting thoughts.

SLIDESHOW: 10 Reasons Why 2017 Will Be the Year of Data Literacy by Dan Sommer via @infomgmt

The growth in data analytics and governance is leading to an increase in the workers that manage and master it all. The result will be a new level of ‘data literacy’ in 2017. Here are 10 reasons why.

I have to agree with him for all his points in varying degrees.

SLIDESHOW: Top 5 Tips for Effectively Deploying IoT Solutions by Dan Jackson via @infomgmt

The Internet of Things will be one of the top IT trends for 2017, but IoT adoption is often difficult. Here are five tips on how to have a smooth and efficient experience.

Repeatable and Scale-able are key (I'm assuming you already know to sort out the Data)

How to build a Successful Big Data Analytics Proof-of-Concept by @GoCloudMoyo via @Datafloq

For all kinds of organisations, whether large multi-national enterprises or small businesses, developing a big data strategy is a difficult and time-consuming exercise. In fact, big data projects can take up to 18 months to finish. While a few within an organisation may be very well aware of what Big Data is and what the possibilities of Big Data are, not everyone else, including the decision-makers, are aware of this.

Useful bullet points in this that are well worth remembering.

WEBINAR: Optimizing Analytical Insights, Data Security and Visualization - 15 December 2016

Overview

Title: Optimizing Analytical Insights, Data Security and Visualization

Date: Thursday, December 15, 2016

Time: 09:00 AM Pacific Standard Time

Duration: 1 hour

Summary

Optimizing Analytical Insights, Data Security and Visualization

How do you gain visibility and insights from all your data when you are faced with analyzing over 4M records from 5 different systems?  Join us for this latest Data Science Central webinar and learn how Erik Miller was tasked with analyzing Western Union’s information security measures and visualizing the data in Tableau. Challenged with over 500,000 locations and high volumes of data in Excel, Access, MySQL and more, the process initially took over 100 hours per month.  Erik will show how he turned a 100 hour process into a 5 minute process while also:

• Seamlessly integrating 36 disparate data sources into Tableau, allowing him to tell a story with all available data
• Gaining analytical insight into risks posed by malicious insiders, hackers and uniformed users
• Building out a flexible and modular analytics program for quicker insights

Brian Dirking -- Product Director -- Alteryx 
Erik Miller -- Sr. Systems Engineer, Cyber Security Analytics -- Western Union  

Hosted by: 

Bill Vorhies, Editorial Director -- Data Science Central

Register here

WEBINAR: Advanced analytics in the era of big data - 15 December 2016

Complimentary Web Seminar
December 15, 2016
2 PM ET/11 AM PT
Hosted by Information Management

Today’s advanced analytic environments are putting greater pressure on decision support infrastructures, creating a mandate for a better, more agile foundation to support them. If you are cracking under the pressure of delivering BI and analytics in a timely way, register for this webinar to hear experts share tips on delivering value to the business faster.

Learn about cutting-edge, data integration and database technologies that simplify the preparation and engineering of data – automating the means by which it is integrated, transformed, and managed – along with the process of manipulating and analyzing data at massive scale.

Topics to be covered include:

• Technologies that enable the rapid and agile integration and processing of data
• How to simplify and accelerate the efforts of data scientists and business analysts
• The role of big data in advanced analytics

Featured Presenters:

Moderator: Eric Kavanagh Information Management	Speaker: Donald Farmer TreeHive Strategy	Speaker: Shawn Rogers Statistica	Speaker: Imad Birouty Teradata	Speaker: Michael Whitehead WhereScape

Sponsor Content From:

Register here

How Big Data Takes the Retail Industry to a Whole New, More Informed Space by @GoCloudMoyo via @Datafloq

Speculation around the future of retail often tends to drift into visions of drones flying through the skies and delivering packages within minutes of a consumer clicking a few buttons on a site. In this projection, the bricks and mortar retail stores are old-fashioned, out of date and a relic of the past. Yet the reality of today’s retail environment is a far cry from that distant future, but with Big-Data-as-a-Service, retail can become a lot better. What kind of insights can be collected with data?

I have to agree - what is the point of getting yet more data when you may not either understand what you have or not have used it properly.

Why Big Data as a Service is the Hottest Trend in Cloud Now by @GoCloudMoyo via @Datafloq

Big data as a service (BDaaS) is an evolution of software as a service (SaaS) and platform as a service (PaaS), with the added ingredient of massive amounts of data. Essentially, the BDaaS offering is a solution for companies to solve problems that they are facing by analysing and interpreting their data. Organisations around the world have warmed to the idea that their next phase of growth will be driven by understanding the insights that are gleaned from the data which is produced by their interactions,

Definitely the way to go.

Harnessing the Power and Complexity of the Configuration Data Exchange by Pater White via @infomgmt

By digitally capturing the current configuration of an asset, additional intelligence can be derived from that information when compared to the expected values using product data attributes or the Digital Thread.

I found this really interesting.

SLIDESHOW: Top 10 IoT Technologies and Trends for 2017 via @infomgmt

The Internet of Things will continue to be one of the largest areas of technology investment in 2017 and 2018, says technology analyst firm Gartner. Here's a look at the top trends to expect.

I definitely agree IOT standards are important.

Telling the Difference Between Good Data and Bad by Berry Ritholtz via @infomgmt

Initial reports, thanks to the National Retail Federation, are a case study in how to obtain meaningless data and then put it to bad use.

Interesting thoughts and something we should all remind ourselves of.

SLIDESHOW: Future History of Machine Learning: A 25-Year Look Forward by Jeremy Achin via @infomgmt

Great advances are being made with machine learning and artificial intelligence, but nothing compared to what the next quarter century has in store. Jeremy Achin, data scientist and CEO of DataRobot shares his thoughts on what we can expect.

Great slideshow of what might/could happen in the future. Can't wait.

How the Singapore Circle Line rogue train was caught with data via @datagovsg

Great data detective story! For months, a train line suffered from mysterious disruptions and created confusion and distress. Here's how a team of data scientists saved the day.

This is a great real life example and shows the results you can get from something when you dig down into the data.

5 architectural principles for building big data systems on AWS by @ConnerForrest via @TechRepublic

If your company is looking to make a bet on big data in the cloud, follow these best practices to find out what technologies will be best for your AWS deployment.

Useful tips

The Critical Importance of Classifying Attributes by Tom Davenport via @Data_Informed

Tom Davenport offers tips if your company’s promotions aren’t succeeding, or if your new product or service success rate is low: Take a cue from aggressive adopters of attribute-based analytics.

Some interesting points.

Deluge Of Data Makes Case for Advanced Business Intelligence by Bob Violino via @infomgmt

The market is moving away from traditional BI processes involving complex spreadsheets toward agile BI systems that offer a deeper understanding of correlations in data.

I definitely agree with him - these days a spreadsheet is just not good enough. The business wants/needs/demands  graphs, dashboards, data across systems joined together, the ability to change the report themselves to drill down.  BI is moving towards self service and whilst it is fine for you to give a good starting point and all the necessary data, today's user is more sophisticated and needs to be able to behave more like a hybrid between a data analyst and a business user.

WEBINAR: Digital mesh or digital mess? Prepping for the future of IoT management - 8 December 2016

Complimentary Web Seminar

December 8, 2016
2 PM ET/11 AM PT
Hosted by Information Management

Sensors, wearables, smart homes, kiosks. The IoT explosion is rapidly transforming the way we serve customers and the way we live our lives.

But if you’re charged with managing and supporting new remote “Digital Mesh” environments that link IoT and smartphones over Wi-Fi, you’re going to face some major challenges. So it’s not too early to assess those impending IoT-related challenges and start strategizing about solutions.

Join us for this thought-provoking session to efficiently learn about the soon-to-arrive future of IoT and the latest thinking about the remote management challenges that it will create, including:

• The new role of IoT in your business
• OS fragmentation in the Digital Mesh
• Wi-Fi as the “new oxygen”
• The coming cost/scale conundrum

You’ll also be able to ask top IoT thought-leaders your own personal questions about how your business should prepare for the future of Digital Mesh.

Featured Presenters:

Moderator: Lenny Liebmann Founding Partner Morgan Armstrong

Sponsor Content From:

Register here

WEBINAR: Analytical Success: Making Smarter Business Decisions From Your Data - 8 December 2016

Webinar Event Details

Date: Thursday, December 8, 2016
Time: 1:00 pm ET/ 10:00 am PT
Duration: 60 minutes (including Q&A)

What You'll Learn Data has become a critical asset for any business in any industry. However, data alone will not drive improved decision-making or better business performance. What is needed is the right data and the right analytics to turn data into business value. Many organizations simply feel lost within the endless data sources and analytics approaches they now have access to because they lack an actionable strategy for using analytical insights to drive better decision-making and performance improvements. This one-hour webinar will explore the development of an analytics strategy that enables the behavioral changes and operational transformation necessary to gain the competitive upper hand on your data. Attend this webinar to: • Understand why data and analytics are a competitive differentiator in every industry • Learn how leading companies turn data into real value • Discover how to apply analytics more strategically to deliver tangible business results • Become aware of the key pitfalls to avoid in data and analytics projects Presenters Bernard Marr,  Bestselling author, keynote speaker, strategic performance consultant, and big data guru, Data Informed Board of Advisers Bernard Marr is a bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI, and big data guru. In addition, he is a member of the Data Informed Board of Advisers. He helps companies to better manage, measure, report, and analyze performance. His leading-edge work with major companies, organizations, and governments across the globe makes him an acclaimed and award-winning keynote speaker, researcher, consultant, and teacher. Radu Miclaus,  Senior Manager Analytics Pre-Sales, SAS Institute Radu is a creative analytics professional with more than 8 years of experience architecting enterprise analytics infrastructure that focus on transforming raw data into actionable insight for National accounts and commercial accounts at SAS Institute. With deep expertise in business application related to risk analytics, supply chain, IoT, customer intelligence and personalization, Radu focuses on engineering platforms that prepare analytics data, model it and deploy analytics decisions back into operations systems at the scale and speed needed by customers. Currently Radu leads a team of data scientists and pre-sales engineers who support customer engagement cycles related to Big Data initiatives using SAS technologies like Grid, In-Database, Hadoop, In-Memory and Event Stream Processing for high-availability, near-real-time and real-time analytics application.  Register here

A Bid Farewell to Blockchain by Henk Jan van der Klis via @infomgmt

Now, on the brink of yet another new year, it's time to bid farewell. If everyone is joining, the party's momentum is here, the peak of inflated expectations around the corner, followed by the Trough of disillusions.

Strange blog - I think the thrust of this article is that everything is now moving towards centralised code and this can be done by anyone and everyone.

To Achieve Advanced Analytics, Start with Big Data Integration by John Thielens via @infomgmt

Big data requires new forms of processing and thus, innovative technology to support and create enhanced decision-making and greater insights. It’s no easy task given the scale at which we’re doing business today.

I know myself from my experience organisations have many disparate systems with the same data in fields with different names, different formats, etc. Integrating all this data is an art which needs careful consideration. In a perfect world everything would be designed to be the same in all the various data source but the world is not perfect.  In order to get insights and value out of all your data you need to integrate it first.

SLIDESHOW: 9 Essential AI Technologies by Mike Gualtieri via @infomgmt

Artificial intelligence is the newest ‘big thing’ in data management, but defining just what AI is isn’t so easy. As it turns out, there are at least nine significant technologies that make up this complex topic.

Some that you will know, some you might not have thought they were in this list.  Worth reading.

Wal-Mart Tackles Food Safety With Test of Blockchain Technology by Olga Kharif via @infomgmt

With the blockchain, Wal-Mart will be able to obtain crucial data from a single receipt, including suppliers, details on how and where food was grown and who inspected it.

This is really exciting and also shows how blockchain can be used for something different to financial systems.

The Foundations of Algorithmic Bias by Zachary Chase Lipton via @kdnuggets

We might hope that algorithmic decision making would be free of biases. But increasingly, the public is starting to realise that machine learning systems can exhibit these same biases and more. In this post, we look at precisely how that happens.

Please note this is a three page long post.

I really like this article and it really makes you think as you read through it - definitely recommended reading.

An overview of gradient descent optimization algorithms by Sebastian Ruder.

"Gradient descent is one of the most popular algorithms to perform optimisation and by far the most common way to optimise neural networks." Here's a look at different algorithms for optimising gradient descent.

This is really clear and useful - you can use it for learning or revision.

WEBINAR: How to create powerful visualisations to explore, share, and analyse data - 1 December 2016

December 1 • 1:00 pm ET/ 10:00 am PT

Organizations need a way to get extremely fast insight from any size data and share it with co-workers of varying skill sets — wherever they happen to be.

In this webinar, learn how to create data visualizations that let everyone — even those without significant analytics skills — explore and analyze data. Users can quickly see connections and correlations, then immediately share results via the Microsoft Office tools they use every day.

 Attend this webinar to examine:

• How common Microsoft Office tools infused with SAS® Visual Analytics capabilities can help you quickly visualize very large amounts of data and share easy-to-understand analytics insight via the web, mobile devices, and Microsoft applications
• How to empower analysts with data preparation and analytics within a familiar environment
• Ways to explore data and glean insight that surpass traditional visualization and reporting, allowing recipients to slice

Register here

WEBINAR: Get Modernized: 5 Steps to Better Analytics - 6 December 2016

Webinar Event Details

Date: Tuesday, December 6, 2016
Time: Noon ET/ 9:00 am PT
Duration: 60 minutes (including Q&A)

What You'll Learn While analytics is not new to business, the technology available today for supporting analytics is new. It has led to a dramatic increase in the speed and scale with which analytics can be performed and integrated with business processes. Missed opportunities to modernize your analytics technology can result in substantial time and resource costs, and can have a significant impact on the quality of your business decisions. In this webinar, Tom Davenport, renowned analytics author, along with analytics leaders from Deloitte, SAS, and Intel, share strategies and steps for modernizing analytics. You can learn how to: • Evaluate the analytics solutions that are available today • Avoid the risks faced by organizations that are a step behind their competitors due to outdated technology • Get started on the path to analytic modernization by following five critical steps Presenters Thomas Davenport,  Co-Founder, International Institute for Analytics Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative on the Digital Economy. and a Senior Advisor to Deloitte Analytics. He teaches analytics and big data in executive programs at Babson, Harvard Business School, MIT Sloan School, and Boston University. He pioneered the concept of “competing on analytics” with his best-selling 2006 Harvard Business Review article (and his 2007 book by the same name). Jordan Wiggins,  Principal, Deloitte Consulting LLP Jordan Wiggins is a leader in Deloitte’s Analytics and Information Management practice. He has more than 15 years of experience in the technology industry with a focus in analytics. Jordan drives strategic, analytics-based solutions that enable clients to utilize raw data more effectively to support the decision-making process. Scott Van Valkenburgh,  Sr Director Partner Relationships SAS With more than 800 partners in the portfolio, Scott Van Valkenburgh leads the organization that is responsible for SAS’ global partner relationships. His teams are responsible for SAS partner go-to-market strategies and execution. Scott is a thought leader in how companies can improve by modernizing their analytic infrastructure, processes and systems. Prior to joining SAS, Van Valkenburgh was the founder and managing partner of the Sequoia Architecture Group and served as a Principal for PricewaterhouseCoopers within the Management Consulting Services Information and Technology Practice. Pat Richards,  Industry Partner Solutions Manager Intel Pat leads Intel Big Data Service Enablement Organization in the South East, helping companies implement and realize true business value with Big Data solutions. Before joining Intel Pat was VP of Professional Services for Canada and US for NCR. He also served as CTO at SCIenergy providing leadership and management of the company's software-as-a-service (SaaS) product development team. Pat spent three years as Vice President, Technical Operations, at Fox Audience Network and before that, ten years at IBM in a number of progressive technology roles in the areas of grid computing, virtualization and Web 2.0.

Register here

WEBINAR: Innovation driven by strategy - 8 December 2016

Webinar Event Details

Date: Thursday, December 8, 2016
Time: 1:00 pm ET/ 10:00 am PT
Duration: 60 minutes (including Q&A)

What You'll Learn The right analytics help to improve business performance. However, not all organisations succeed every time in gaining tangible value from their data. What is often missing from the analytics equation is an actionable strategy for using analytical insights to drive better decision-making. This one-hour webinar will explore the development of an analytics strategy, enablement of behavioural changes and operational transformation to gain the competitive upper hand. • Presenters Bernard Marr,  Bestselling author, keynote speaker, strategic performance consultant, and big data guru, Data Informed Board of Advisers Bernard Marr is a bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI, and big data guru. In addition, he is a member of the Data Informed Board of Advisers. He helps companies to better manage, measure, report, and analyze performance. His leading-edge work with major companies, organizations, and governments across the globe makes him an acclaimed and award-winning keynote speaker, researcher, consultant, and teacher. Radu Miclaus,  Senior Manager Analytics Pre-Sales, SAS Institute Radu is a creative analytics professional with more than 8 years of experience architecting enterprise analytics infrastructure that focus on transforming raw data into actionable insight for National accounts and commercial accounts at SAS Institute. With deep expertise in business application related to risk analytics, supply chain, IoT, customer intelligence and personalization, Radu focuses on engineering platforms that prepare analytics data, model it and deploy analytics decisions back into operations systems at the scale and speed needed by customers. Currently Radu leads a team of data scientists and pre-sales engineers who support customer engagement cycles related to Big Data initiatives using SAS technologies like Grid, In-Database, Hadoop, In-Memory and Event Stream Processing for high-availability, near-real-time and real-time analytics application.  Register here

GPS, IoT, and the Future Tech that Could Replace it All by @audgepauge93 via @Datafloq

Whether you’re lost on a lonely country road, or simply want to check into a cute café in New York City, GPS always has your back. Now that it’s so fully integrated into our cars, our phones, and our lives, it can be hard to remember a time before location services were available on almost every device. Besides making it tough to get lost as long as your battery lasts, GPS has become more sophisticated and useful than we could have imagined twenty years ago, but where will it go 20 years from now?

I like this idea of IoT being used with GPS to create something like GPS Plus.  I think the future might be interesting.

WEBINAR: The DNA of a Data Science Rock Star - 29 November 2016

Overview

Title: The DNA of a Data Science Rock Star

Date: Tuesday, November 29, 2016

Time: 09:00 AM Pacific Standard Time

Duration: 1 hour

Summary

The DNA of a Data Science Rock Star

Data Scientists are tasked with transforming their organizations with data. Yet many are struggling to realize their true Rock Star potential, and organizations are missing out on what these Rock Stars could do with the right environment.

Join us for this latest Data Science Central Webinar and learn what skills, tools, and behaviors are emerging as the DNA of the Rock Star Data Scientist. We will explore best practices for Big Data Analytics through Open Source technologies (i.e. Apache Spark, R, R Studio, Python, Jupyter), techniques including machine learning and behaviors around collaboration, sharing and learning.

Speakers:
Carlo Appugliese, Hadoop & Spark Evangelist -- IBM Analytics 
Greg Filla, Associate Offering Manager, Data Science Experience -- IBM Analytics

Hosted by: 

Bill Vorhies, Editorial Director -- Data Science Central

Register here

3 challenges for artificial intelligence in medicine Brandon Ballinger via @OReillyMedia

Here's how we can overcome the dearth of labelled data, deployment issues, and regulation fears in order to increase the use of AI in health care.

I like this and I can definitely see that there could be huge advances if we use AI in order to advance medical treatment and care.

A Look at Insurance's Big Data Trajectory by John McCormick via @infomgmt

Mitch Wein, VP of research and consulting at Novarica, sat down with Editorial Director John McCormick to discuss where insurance carriers are with the technology and where he sees them going in the near-future.

This is interesting and I can definitely see that insurance has a lot to learn from big data.

Blockchain And IoT: Not Ready For Primetime, But Now’s The Time To Start by @martha_bennett

Well-architected blockchain-based systems can help deliver those requirements, but they’re not available or even feasible today. In many ways, that’s a good thing, because it opens up great opportunities.

I really like this blog and she is definitely saying the kinds of things I agree with so I advise everyone to read it.

How Artificial Intelligence Will Redefine Management by Vegard Kolbjørnsrud, Richard Amico and Robert J. Thomas via @HarvardBiz

How can managers, from the front lines to the C-suite, thrive in the age of AI? To find out, the Harvard Business Review surveyed 1,770 managers from 14 countries and interviewed 37 executives that are responsible for digital transformation at their organisations. Here's what they discovered.

I found this really interesting. It definitely seems clear to me that any business needs AI and/or machine learning in order to get competitive edge and be able to gain and keep customers. In order to that and understand the need and outputs management need to understand and use these tools.

How Bayesian Inference Works by Brandon Rohrer via @kdnuggets

Bayesian inference isn’t magic or mystical; the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer. Read an in-depth overview here.

I really enjoyed reading this as it reminded me of some aspects that I had either forgotten or didn't appreciate fully.

Top 10 Amazon Books in Data Mining, 2016 Edition by Matthew Mayo via @kdnuggets

Given the ongoing explosion in interest for all things Data Mining, Data Science, Analytics, Big Data, etc., we have updated our Amazon top books lists from last year. Here are the 10 most popular titles in the Data Mining category.

Definitely worth considering these books if you look at the contents list and can see areas you been to learn or brush up on.

SLIDESHOW: 6 Best Practices for Managing BYOD Technology by Richard Allen via @infomgmt

The mobile workforce population is expected to surpass 105 million by 2020, according to IDC. Keeping all those workers and devices from causing security risks is becoming increasingly hard. Here are 6 tips on how to best manage it all.

I definitely agree with him that prevention is better than cure.

France Creates Big Brother Data File Raising Privacy Concerns by Alexandre Boksenbaum-Granier via @infomgmt

Anyone with an identity card or a passport will be registered in the new database. A single file will hold details including name, height, and eye color, along with bio-metric information such as finger prints.

Wow - this could become a hackers paradise.

Big Data Is All Relative—or Relational by Mike Azevedo via @infomgmt

But as we foam at the mouth over the next great revelation that will emerge from the Hadoop cluster, a new wave of cloud-enabled applications are testing the limits of our traditional relational database systems.

RDBMS are so ensconced into our systems that it has to be better to have new innovations able to use them rather than the expense of redeveloping every thing . Yes I admit things would work better and faster with the new databases, but sometimes there is not the time nor the resources to move the data.

WEBINAR: Getting Your BI to Deliver Actionable Insights.- 21 November 2016

Join the Live Webinar

Date: Monday, November 21, 2016, 1:00 p.m. EST
Presenters: Boris Evelson, VP Principal Analyst at Forrester Research & Sisense Head of Product Strategy, Ani Manian

Organizations are growing their data environments up to 50% a year, in both size and scope. Yet only a fraction of this data is actually being translated into actionable insights and better decision making. So how do you achieve actionable insights from your BI?

• Translate growing data into actionable insights and better organizational decision making
• Uncover the latest discoveries in BI, Agile BI, big data and artificial intelligence
• Discover best practices for merging business and technology management, to receive valuable insights from your BI
• Register here

Big Data and Low Expected Returns by Matt Levine via @infomgmt

What is interesting about "big data" is how it has changed what information is useful, and to which investors.

Interesting - I'm tempted to want to go play with all that data.

SLIDESHOW: 7 Reasons Why Data Science Lacks Ethics, and How to Retrofit Morality by Dave da Silva via @infomgmt

Capgemini Senior Data Scientist Dave da Silva dicsusses the reasons why big data and data analytics seem to have abandoned ethics, and what can be done to correct the situation

I particularly like Slide 8 because organisations run the same reports over and over again and if they no longer provide value or insights they should not be run using up resources.

The Competitive Landscape for Machine Intelligence by Shivon Zilis and James Cham via @HarvardBiz

Two years ago, Shivon Zilis of Bloomberg Beta first published her widely circulated report, The Current State of Machine Intelligence. In this year's update, Shivon Zilis and James Cham offer insights into how the "Stack" of building blocks is maturing and what all businesses need to do NOW in order to survive and outlast their competitors. This is a must read for everyone interested in the business of this rapidly evolving space.

This is great and definitely s must read.

SLIDESHOW: 19 Top Companies for Enterprise Content Management by David Weldon via @infomgmt

Which are the top companies for enterprise content management? Gartner Group thinks it knows, and has released its Magic Quadrant for the top 19 Enterprise Content Management vendors.

Interesting, particularly the smaller ones towards the end.

The End of Analytics? by Thomas H. Davenport via @Data_Informed

Thomas H Davenport looks at the trend of companies (Salesforce is an example) providing self service analytics capabilities.

I found this really interesting.

WEBINAR: Big data, cognitive bias, and data quality’s new frontiers - 15 November 2016

Big data, cognitive bias, and data quality’s new frontiers

Complimentary Web Seminar
November 15, 2016
11 AM ET/8 AM PT
Hosted by Information Management

For many years we’ve treated data quality as a set of measurements related to a specific set of data (Is it complete? Is it valid?) or at the intersection of two sets of data (Are they consistent?). But with the advent of Big Data, we suddenly face a deluge of data from known and unknown sources, with highly varied formats, and potentially very disparate meanings and uses. Into this mix we add the human factor, the individual sets of assumptions and biases that are both built into the systems producing the originating data and incorporated into the integration and interpretation of the resultant data.

Working from the assumption that all this Big Data is supposed to yield more insight and better business decisions, how do we ensure that we can trust not only the original data, but the subsequent data we’re acting upon? To address this challenge, we need to consider new frontiers and dimensions for data quality to ensure that the Big Data we are using is not only relevant and fit for purpose, but data that we can trust and act confidently upon.

Featured Presenters:

Moderator: Jim Ericson Editor Emeritus Information Management	Speaker: Harald Smith Director, Product Management Trillium Software

Sponsor Content From:

Register here

Master Data Management Sees Large Gains Among Special Interest Groups by David Weldon via @infomgmt

There has been a considerable uptick in job openings on the web, in social media that reference master data management and data governance, and in membership for MDM and data governance groups

I've seen that with recruitment agencies - if you have MDM on your LinkedIn or CV they are emailing and calling more.

Open Source Data Sharing Software Takes Aim At Cancer by Fred Bazzoli via @infomgmt

The new resource can assist investigators in sorting through genomic cancer data to determine better methods of cancer prevention, diagnosis and treatment.

This looks really exciting and I believe could also be used for other illnesses than cancer.

Investing in Data: How Tomorrow’s Companies Profit from Data Centricity by Michael Pumper via @infomgmt

Tomorrow’s world is all about data, and today’s companies should consider becoming data-centric to remain relevant.

This is not the time for existing companies to sit on their laurels and carry on as normal. Today is about using the internet of things to monitor objects and processes, artificial intelligence and machine learning to get an insight out of data in order to gain a competitive edge - without these your business will fail.

Organizations Turn Focus to Data Reliability, Security and Governance by David Weldon via @infomgmt

With the rapidly growing investments in data analytics, many organisations complain they lack a combined view of all the information being created.

I'm so glad these areas have more focus - you wouldn't let a pilot fly the plane you are in if he hasn't passed all his exams after training so why are you risking you business by making decisions on data that is not managed properly?  However I would point out that apart from the points raised in this article you need to validate your data to make sure it is good quality.

SLIDESHOW: Gartner Identifies Five Domains for the New Digital Platform by David Weldon via @infomgmt

If organisations are to succeed in the future, they must embrace a new type of “civilisation infrastructure,” insists Gartner Group’s Peter Sondergaard. Speaking at the Gartner ITxpo in Orlando last week, Sondergaard explained what this means for chief information officers today.

I can completely agree with the observations in this article from Information Management.

WEBINAR: The citizen data scientist: Can you democratize analytics for better business outcomes? - 10 November 2016

The citizen data scientist: Can you democratize analytics for better business outcomes?

Complimentary Web Seminar
November 10, 2016
2 PM ET/11 AM PT
Hosted by Information Management

Analytics is about better understanding customers, markets, and other phenomena that impact business performance. So while PhDs in mathematics and computer science play an important role in analytics success, employees with degrees in psychology, economics, and other fields can also help your company find nuggets of actionable insight in the mass of Big Data.

Join our special webinar on “The Citizen Data Scientist” to learn how the most digitally savvy organizations are leveraging their non-technical talent. Key takeaways will include:

• How to identify top potential non-IT contributors to your analytics initiatives
• What it takes to transform a liberal arts major into an analytics superstar
• Why “democratization” of analytics is a hot trend among Digital First market leaders

You’ll also be able to directly ask our expert panel questions about your own most pressing analytics and BI challenges. So sign up today!

Featured Presenters:

Moderator: Lenny Liebmann Founding Partner Morgan Armstrong

Sponsored By:

Register here

WEBINAR: The Secret to "Enterprise-Grade" Digital Transformation - 10 November 2016

Webinar Event Details

Date: Thursday, November 10, 2016
Time: Noon ET/ 9:00 am PT
Duration: 60 minutes (including Q&A)

What You'll Learn Digital transformation is all the rage today, impacting everyone from the C-suite to the Ops team. Customer pressure and a turbulent business environment are driving IT departments to adopt a broad array of cutting-edge computing technologies. In this mad race to competitive advantage, however, pitfalls abound — immature technologies, archaic business processes, and a lack of visibility into the real-time behavior of businesses are impeding the path to success. What’s missing? An “enterprise-grade” IT structure that places digital priorities into the heterogeneous, middleware-connected, legacy-heavy enterprise context. Companies who effectively master mission-critical tools such as enterprise-grade transaction tracking and real-time application analytics will keep pace with — and remain in control of — the tide of change sweeping across their industries. Those who do not will stumble. With decades of experience exploring the fast-changing landscape of IT technology, leading industry analyst and Forbes contributor Jason Bloomberg will discuss what it means to be “enterprise-grade” and how businesses must leverage enterprise-grade technologies to pursue tangible business outcomes such as: • More sophisticated and reliable real-time digital business services • Greater alignment between IT analytics and business goals • Improved compliance and fraud detection Following Jason, Nastel Technologies’ Charley Rich will share several real-world customer examples where enterprise-grade transaction tracking and analytics capabilities resulted in better, game-changing business outcomes.

Presenters Jason Bloomberg, is a leading industry analyst and globally recognized expert on agile digital transformation. He writes and speaks on how today’s disruptive enterprise technology trends support the digital professional's business transformation goals. He writes for Forbes, his biweekly newsletter called the Cortex, and contributes to several blogs. He also helps technology vendors and service providers communicate their digital transformation stories. His latest book is called The Agile Architecture Revolution (Wiley, 2013). Mr. Bloomberg has published over 900 articles, spoken at over 350 conferences, webinars, and other events, and has been quoted in the press over 1,500 times. Charley Rich, VP Product Management at Nastel Technologies and jKool has extensive experience in Big Data Analytics, SaaS, UI and APM. He was an important contributor to four highly successful start-ups including: InterWorld, Tivoli, SMARTS and Collation/IBM and holds a patent for Application Performance Monitoring. Prior to Nastel, he was IBM’s World-wide Product Manager for the Application Dependency Discovery Manager solution and received the Tivoli General Manager's Award.

Register here

Three blockchain articles by @VanRijmenam from @Datafloq

In this series of posts, he is providing insights in a technology that will change our world. Blockchain has been said to be as important invention as the Internet and Johann Palychata, a research analyst from BNP Baripas, called Blockchain an invention like the steam or combustion engine.

In part 1 of this series he gave an introduction to Blockchain, in part 2 he provided insights in different types of Blockchain and consensus algorithms and in part 3 he will discuss some of the major challenges we will need to overcome to make Blockchain truly change our world for the better.

This is definitely a must read as this is clearly going to be the future,

Operational data governance: Who owns data quality problems? by David Loshin via @SASsoftware

Data integration teams often find themselves in the middle of discussions where the quality of their data outputs are called into question. Without proper governance procedures in place, though, it's hard to address these accusations in a reasonable way. Here's why.

I completely agree with the second point he makes at the end of the article - far too many times I've worked on a data warehouse project where that team is concerned about the data quality far more than the source system team - to my mind that is wrong.

‘Rogue Algorithms’ and the Dark Side of Big Data via @whartonknows

Most of us, unless we’re insurance actuaries or Wall Street quantitative analysts, have only a vague notion of algorithms and how they work. But they actually affect our daily lives by a considerable amount.

I found this fascinating - we need to do far more auditing of algorithms used so that we are sure and understand what we are doing and the decisions we make are right.

Deep Learning Key Terms, Explained by Matthew Mayo via @kdnuggets

Gain a beginner's perspective on artificial neural networks and deep learning with this set of 14 straight-to-the-point related key concept definitions.

A great list of terms that you need to read and learn from.

Success With Big Data Starts With Asking the Right Questions by David Weldon via @infomgmt

Many organisations complain they aren't achieving the success with big data projects they hoped for. Information Management spoke with Maana's Tara Prakriya about why that is, and what can be done about it.

I agree completely - this is not a vanity project but has to be something to answer specific questions that have benefits that can be measured.

SLIDESHOW: Gartner’s Top 10 Strategic Technology Trends for 2017 by David Weldon via @infomgmt

In its second set of major technology predictions for 2017, Gartner Group yesterday revealed its “Top 10 Strategic Technology Trends for 2017,” which followed the “Top 10 Predictions for IT in 2017 and Beyond.” Gartner defines a strategic technology trend as “one with substantial disruptive potential that is just beginning to break out of an emerging state into broader impact and use, or which are rapidly growing trends with a high degree of volatility reaching tipping points over the next five years.”

Another interesting set of predictions from Gartner that I tend to agree with although there are a few supprises in there.

WEBINAR: What People REALLY Do with the Internet of Things and Big Data - 3 November 2016

Overview

Title: What People REALLY Do with the Internet of Things and Big Data

Date: Thursday, November 03, 2016

Time: 08:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

What People REALLY Do with the Internet of Things and Big Data

Are you developing a winning Internet of Things (IoT) strategy? Or are you being outflanked by the competition again?   IoT is a huge market expansion that will hit $14 trillion by 2020.  A lot of that is in your industry.  The Internet of Things market expansion is a chance to get out in front of the competition.  Sadly, some will take a wait and see approach on IoT until others take the lead.   A robust IoT initiative can move your company from the sidelines to market leadership.  And all this means big data is getting a lot bigger. 

This IoTCentral Webinar digs deep into real world implementations.  Experts will discuss the IoT research results from clients with hands-on implementations.  It all starts with the business drivers that lead to actual projects.  Later the focus shifts to technical drivers and the implications.  Real implementations illustrate the value of analytics.  Come find out what happens when big data meets the Internet of Things.

Attendees will learn:

• The business drivers of end-user organizations implementing IoT
• Who are the champions driving IoT initiatives? Hint: It’s not IT
• Popular devices being monitored with sensor data    
• Discover which analytics are applied to sensor data  
• Which analytical platforms are supporting IoT initiatives
• How many organizations are already on their second IoT project   

Speakers:
John L Myers, Managing Research Director of Analytics , Enterprise Management Associates
Dan Graham, Director of Technical Marketing  -- Teradata
 

Hosted by: 

David Oro, Editorial Director -- IoT Central

 

  

Register here