Putting the promises of artificial intelligence to the test by Kishore Durg via @infomgmt

As enterprises use technology to become more agile and competitive, artificial intelligence is quickly gaining a multitude of use cases. Artificial intelligence can take on a range of tasks – from automating routine business processes to handling complex customer service queries – freeing us to tackle more thoughtful work.

I agree - there is a need for careful testing that is appropriate for the technology - so traditional testing might not be appropriate.

5 steps for success in creating MDM data governance teams by David Weldon via @infomgmt

Many organisations are challenged at how to best establish a successful governance strategy around their master data management efforts. It starts with the right individuals and attitude.

I think some of these steps can be expanded into steps themselves and therefore need a lot of time and thought to detail and break down. However this is a good starting point that can help to drive the areas you need to include in your strategy moving forward.

Complying with Europe’s other data management mandate – MiFID II by Marianna Shafir via @infomgmt

The new regulations affect any organisation that operates or does business with firms that provide investment services in the European economic area.

Something very important that I believe we either don't know about or forget.

Three important lessons about introducing software robotics by Dennis Walsh via @infomgmt

For a successful rollout, CIOs need to work with the C-suite and reassure the rank and file

His 2nd point is very apt - you really have to start small, try it out, get a success, then start to expand and roll it out slowly. Thing carefully when choosing something to start with - the success of what you choose will affect the entire aim of implementing software robotics.

These 3 business functions will be the first to benefit from artificial intelligence by Bas de Vos via @infomgmt

The key to success lies in combining machine and human intelligence says the director of IFS Labs.

Three examples of areas that wil benefit hugely from the implementation of AI and ML in order to get some kind of benefit, cost saving or advantage. I can definitely see the second example in this article being very worthwhile. Adding IoT, AI and ML together in a manufacturing environment huge savings could be made around maintenance (both preventative, predictive as well as a break/fix scenario). Minimising downtime is key to saving lost revenue and I'm convinced it costs less to fix a problem just before or as soon it appears as opposed to after it has occurred and the chance of associated breakages that are caused by the original problem.

Growing skills gap taking toll on data management strategies by Bob Violino via @infomgmt

Nearly half of firms recently surveyed struggle to identify between data truths and manipulations. This indicates an urgent need to upskill and support workers, the report said.

I agree - you have got to understand your data if you are going to use it and make good decisions based from reports using it.

5 security strategies that can cripple an organisation by Bret Settle via @infomgmr

In their urgency to address vulnerabilities, many organisations are making critical mistakes—the results of which can mirror data breaches in their lasting, negative impact.

I agree with Bret - it's hard to protect what you were not aware of (like a silo or a system developed by the business), and how do you protect and prevent all sorts of security issues without adequate finance, resources or even adequately trained resource. 

WEBINAR: Semantics and Cognition for Visual Analytics - 24 July 2018

Semantics and Cognition for Visual Analytics Join us for this latest DSC Webinar on July 24th, 2018

Semantics is an area of linguistics and natural language processing to help make sense and meaning of the world around us. In visual analytics, using principles of semantics can help improve the meaning and overall cognition of a visualisation to the user.  In this Data Science Central webinar, we will discuss how we are thinking of adding semantics to help enrich various aspects of the visual analytics workflow. By incorporating and inferring general concepts to empowering users to add domain-specific knowledge, semantic governance can bring more meaning to the analytical experience.  Speaker: Vidya Setlur, Manager, NLP Team -- Tableau Hosted by: Bill Vorhies, Editorial Director -- Data Science Central Title:  Semantics and Cognition for Visual Analytics Date:  Tuesday, July 24th, 2018 Time:  9:00 AM - 10:00 AM PD

Register here

Data Warehouse or Data Lake? When to Use Each by @LimiMaayan via @Datafloq

What platform should you use to power your data analytics machine? Data warehouses and data lakes are common two alternatives.

Some thoughts to help you decide between the two. Many analytics rely on the data having some kind of structure which points more towards a data warehouse, but I can also see that you can discover new things when you do more with unstructured data (data lake). It really depends on what you are trying to do.

How organizations can develop an AI governance strategy by Vikram Mahidhar via @infomgmt

With the ability of artificial intelligence to arrive at its own conclusions, governance over the machines is critical for the sake of business executives and customers alike.

Vikram makes some really great points in this article and I think it is well worth putting in lace in your organisation as a minimum quickly before anything is done before the strategy/process/controls are in place.

7 surprising companies where you can work on cutting-edge AI technology by Ben Dickson via @TheNextWeb

Consider yourself lucky if you happen to be studying machine learning, data science, business intelligence, or any other field that relates to AI. While automation slowly eats away at human jobs, the demand for AI talent continues to grow at an accelerating pace.

If nothing else this teaches us not to assume who might or might not use AI in their business. However it also can point us towards the fact that AI could be the solution to a problem - you just haven;t thought of it yet.

5 Data Science Projects That Will Get You Hired in 2018 by @DataOptimal via @kdnuggets

A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.

You still have to come up with the subject of these projects but this is a good shopping list of the types of project and the skills you need to display as part of your project work. Very useful and I suggest you bookmark this and refer back to it.

5 predictions for when big data will become everyone's job by Larry Alton via @infomgmt

Even the best predictive analytics platforms will still need a human mind to tackle high-level analysis. Look for major changes in almost all human roles to come.

Some really great observations in this article that definitely warrants the time to read and think about what he has listed.

How Artificial Intelligence is changing the Farms of Future by @webtunix​ via @Datafloq

AI has become an agent for revolutionising the agricultural industry. AI has introduced new technological trends making farming highly productive

Some interesting observations on who AI can (and already is in some cases)  modifying how we farm in order to maximise the yield per acre. I'm not sure that the average farmer would use this kind of technology but as the younger generation comes on board I see no barrier (apart from the obvious one of cost) to stop there kinds of developments.

If you thought GDPR was bad – Just wait for ePrivacy Regulation by Lisa Loftis via @infomgmt

Regulators developed ePR because the volume and complexity of digital data are increasing exponentially and the environment for generating, storing and consuming it can be quite different from more traditional formats.

I like this explanation although as the author states it is still being negotiated at the moment. I'm sure the recent Facebook data problem has given many a clearer perspective on the need for some form of standard and documentation.

Bamboozled by the analytics and BI Magic Quadrant? Four things to do by Cindi Howson via @infomgmt

In our summits this year, we sometimes asked how many of you have read the Magic Quadrant (MQ). A mere 20 percent raised their hands in one. I was gob smacked, and could not hide my dismay.

There is a link in the article which points to Cindi's historical blog explaining the 4 mistakes to read when looking at the MQ report.  To get a copy of it you will need to go through an organisation and sign up to something to access it (if you are not a Gartner member) - I would suggest looking on the internet via a search engine or I'll give you two examples here.  Sisense or Qlik

The future of consumer MDM: Cloud, referential matching and automation by Joaquim Neto via @infomgmt

This combination of these three features will put organisations on a good path towards realising real benefits from their master data management strategies.

A good article worth reading. I definitely think automation is the way to go because it ensures that MDM is done,  done properly and that you can match records across the organisation in such a may that there is only one one version of the truth.  One master version of something is often a very difficult thing to achieve in some organisations and that is something that we have to stop.

For SMBs, GDPR could be the best thing that ever happened to data by Kris Lahiri via @infomgmt

New regulatory compliance helps businesses retain users, promotes company innovation and provides an opportunity to overhaul obsolete systems, making them more efficient and driving long term growth.

I have to admit I never really thought to the same depth as Kris has because I was more fixated on the cost that SMB would have to bear without much in the way of benefits to make it a more worthwhile exercise. So this article is good for remind us of the advantages SMBs will get from GDPR compliance.

RQ — The measure of organisational readiness for automation and AI by @jgownder via @Forrester

These technologies are transforming business processes and operating models. But most companies don’t have the competencies to implement them successfully.

There are links for a great sounding webinar and a report at the end of this article by JP that fit very well into this subject.

I really like the PLOT framework which is very well described here.