How natural language processing can transform business intelligence by Alberto Pan via @infomgmt

NLP has the potential to enable true self-service BI by seamlessly translating spoken commands into SQL or any other technical query language. 

I great read which I really enjoyed.

WEBINAR: Cutting Time, Complexity and Costs from Data Science to Production - 6th February 2019

WEBINAR Cutting Time, Complexity and Costs from Data Science to Production REGISTER NOW

One-click (really!) deployment to production without any heavy lifting from data and DevOps engineers Wednesday, February 6 at 8am PT Imagine a system where one collects real-time data, develops a machine learning model… Runs analysis and training on powerful GPUs… Clicks on a magic button and then deploys code and ML models to production… All without any heavy lifting from data engineers. Today, data scientists work on laptops with just a subset of data and time is wasted while waiting for data and compute. It’s about efficient use of time! Join Iguazio and NVIDIA so that you can get home early today! Learn how to speed up data science from development to production: Access to large scale, real-time and operational data without waiting for ETL Run high performance analytics and ML on NVIDIA GPUs (Rapids) Work on a shared, pre-integrated Kubernetes cluster with Jupyter notebook and leading data science tools Featured Speakers: Yaron Haviv, CTO, Iguazio Or Zilberman, Data Scientist, Iguazio Jacci Cenci, Sr Technical Marketing Engineer, NVIDIA Register here

Open sourcing wav2letter++, the fastest state-of-the-art speech system, and flashlight, an ML library going native by/via via @fbOpenSource

The Facebook AI Research (FAIR) Speech team is sharing the first fully convolutional speech recognition system. It uses convolutional neural networks (CNNs) for acoustic modeling and language modeling, and is reproducible. The team says that wav2letter++ is composed only of convolutional layers, which yields performance that’s competitive with recurrent architectures.

There are two articles linked of the landing page from the links in this post. This reads as a great achievement and looks very interesting.

WEBINAR: Optimize The Data Supply Chain - 31st January 2019

Optimize The Data Supply Chain Join us for the latest DSC Webinar on January 31st, 2019 Every organization is aiming to produce more comprehensive understanding of their customers, their business operations and their risks, through data. Most organizations are still learning best practices that allow them to leverage in-house data science resources more effectively. A big piece of the puzzle is enabling better collaboration between data science teams and the lines of business. A team-driven approach is necessary to help. In this latest Data Science Central webinar, led by Mike Ferguson of Intelligent Business Strategies Limited, an independent analyst and consultant who specializes in BI, analytics, data management and big data, you’ll learn: What it means for an organization to be ‘data intelligent’ – and what it takes to get there Optimization of the data supply chain that can help create insight and foresight How a team-driven approach reduces two of the most costly enterprise resources: data and effort Best practices for data science groups to easily find and understand curated and trusted data sets to feed and influence their predictive models A brief overview and demo of Datawatch’s integrated platform that combines best-in-class self-service data preparation, a centralized data marketplace, predictive analytics and data governance Speakers: Mike Ferguson, Managing Director -- Intelligent Business Strategies Michael Rowley, Director Product Marketing -- Datawatch Angoss Ellen Wilson, Product Marketing Manager -- Datawatch Angoss Hosted by: Bill Vorhies, Editorial Director -- Data Science Central   Title:  Optimize The Data Supply Chain Date:  Thursday, January 31st, 2019 Time:  9 AM - 10 AM PST

Register here

3 Major Ways the Internet of Things is Revolutionising E-Commerce by Manish Dudharejia via @Datafloq

IoT has already made its presence felt across various industries. How is it impacting the e-commerce industry?

I'm sure we are already interacting with IoT online we might just not be realising it.

Strong data quality key to success with machine learning, AI or blockchain by Tendü Yoğurtçu via @infomgmt

Enterprises must be skeptical of data as it essentially determines how the AI will work and bias in the data may be inherent because of past customers, business practices and sales.

The past bias could be inherent in the data due to the design of legacy systems, the team typing it in, the customers, the way it was governed by the business or a combination of them.  Historic data should therefore always be treated with great suspicion until you have completed an exercise to check the systems, the data meanings, standards and governance. Please don't make huge business decisions based on data you can't prove it clean and unbiased.

A Radical New Neural Network Design Could Overcome Big Challenges in AI by Karen Hao via @techreview

Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in health.

This is a really interesting development and looks like a great idea. I'm excited for the things that might be possible using this technique.

SLIDESHOW: 10 top technology trends that will impact organisations in 2019 by Mathias Golombek via @infomgmt

Machine learning, data-centricity, self-service BI and distributed ledger technology will be among the top technology trends driving innovation and digital transformation this year.

A great presentation that will give you a good indication of what is coming and you should be thinking about.

8 trends that will impact data management strategies in 2019 by Satyen Sangani and Aaron Kalb via @infomgmt

As organisations continued to see data volumes explode and an increasing number of employees need access to critical information, data cataloguing considerations shifted from being a department level concern to an enterprise critical issue.

A great list of trends in this article.

WEBINAR: Data Prep & Automated ML: Better Predictions For Consensus - 22 January 2019

Data Prep & Automated ML: Better Predictions For Consensus Join us for the latest DSC Webinar on January 22nd, 2019

Financed smartphones are a magnet for identity theft, leaving retailers in the digital and telecommunication industry vulnerable to fraud. Consensus, a Target-owned subsidiary, has developed a highly accurate solution to identify fraud at the point-of-sale before it happens. In this latest Data Science Central webinar, you will learn how Consensus put together agile processes on a cloud analytic solution leveraging Trifacta data preparation and DataRobot automated machine learning to prevent fraud. Attendees will learn: How Consensus developed an AWS cloud-based solution The role of data preparation in supplying accurate data for machine learning models How automated machine learning can drive more accurate predictions Consensus’s time-saving ROI from building models, deploying them on AWS, and the improvement in accuracy and recall Speakers: David McNamara, Lead Product Specialist -- Trifacta Harrison Lynch, Sr. Director of PM -- Consensus Corporation Rajiv Shah, Data Scientist -- DataRobot Hosted by: Bill Vorhies, Editorial Director -- Data Science Central   Title:  Data Prep For Data Ops: How To Select & Deploy Date:  Tuesday, January 22nd, 2019 Time:  9 AM - 10 AM PST

Register here

Mastering the 12 agile software development principles by Anthony Coggine via @infomgmt

We explore the 12 core principles of agile software development outlined in the Agile Manifesto to help you make sense of the sometimes esoteric text.

Interesting thoughts and well worth a read to check you are following all of the principles.

Firm Led by Google Veterans Uses A.I. to ‘Nudge’ Workers Toward Happiness by Daisuke Wakabayashi via @nytimes

Three former Google employees are pitching an AI system designed to increase employee satisfaction at work.

A great use of AI and ML that will hopefully provide the right nudges in order to make people do the right thing to motivate their staff.

WEBINAR: Accelerating Machine Learning on Databricks - 15 January 2019

[Webinar] Accelerating Machine Learning on Databricks Thursday, January 15 at 10am PT We all know it: the potential for Machine Learning practitioners to make a breakthrough and drive positive outcomes is unprecedented. But how do you take advantage of the myriad of data and ML tools now available at your fingertips? How do you streamline processes, speed up discovery, share knowledge, and scale up implementations for real-life scenarios? In this webinar, we will cover some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine Learning. We'll show you how to: Get started quickly using the Databricks Runtime 5.0 for Machine Learning Track, tune, and manage models, from experimentation to production with MLflow Scale up deep learning training workloads from a single machine to large clusters for the most demanding applications using the new HorovodRunner Featured Speakers Adam Conway, VP Machine Learning, Databricks Hossein Falaki, Software Engineer, Databricks

Register here

7 master data management certifications that will pay off by Thor Olavsrud via @CIOonline

Individuals with expertise in master data management (MDM) are essential to helping organisations get the most out of their data and comply with regulations. Here are the MDM certifications that will give your career an edge.

Something to think about if MDM is an area you want to move into.

Mastering MDM is mandatory for digital transformation success by Scott Taylor via @infogmt

Master data is the vital difference between scaling or failing in this time of business disruption and non-stop data.

I agree with Scott - you fundamentally need to change the company culture and processes in order to make sure that this in par of what you do and accurately reflects the organisation as a whole.

The 23 Most Influential Business Intelligence Blogs via @Better_Buys

This list is from Better Buys.

Some useful ones to add to your reading list.

Four fundamentals of workplace automation by Michael Chui, James Manyika and Mehdi Miremadi via @McKQuarterly

Automation occurs in stages. While full automation might still be a ways off, there are many workflows and tasks that lend themselves to partial automation. In fact, McKinsey estimates that “fewer than 5% of occupations can be entirely automated using current technology. However, about 60% of occupations could have 30% or more of their constituent activities automated.”

It's heartening to read that jobs will not be completely replaced - so modified I can live with.

A Guide to Decision Trees for Machine Learning and Data Science by @GeorgeSeif94 via @kdnuggets

What makes decision trees special in the realm of ML models is really their clarity of information representation. The “knowledge” learned by a decision tree through training is directly formulated into a hierarchical structure.

Bookmark this so you can refer back to it when needed. Add him in Twitter for some great help and information too.

Consolidating data silos: What enterprises need to know to harmonise data by Miika Mäkitalo via @infomgmt

The more disparate silos an organisation has, the more vulnerabilities are likely to exist across the organisation.

This is an area that needs careful consolidation and integration into the rest of your data. If you invest the time and money to do that you will achieve some benefits.

What Great Data Analysts Do — and Why Every Organisation Needs Them by Cassie Kozyrkov via @HarvardBiz

Full stack data scientists and machine learning pros get all the glory. But this Harvard Business Review article argues that instead of asking your analysts to develop machine learning skills (risking mediocrity in two fields rather than excellence in one), your analysts should be encouraged to excel at analysis.

Cassie makes a very good point - do you really want a Jack of all trades who is not great at what they do or do you want an expert in the one thing (analysis) that can produce something that is worth risking your businesses future on?

Netflix machine learning director talks personalisation software by Holden Foreman via @StanfordDaily

“Applying machine learning to data solicited from users allows Netflix to proactively reach their audiences.” Netflix machine learning director, Tony Jebara, explains.

This all sounds really exciting - what a great use of all the data they readily have available to them.