WEBINAR: Classify Non-Human Voice Audio for Automation and Embedded Machine Learning - 12 August 2022

Workshop Series Classify Non-Human Voice Audio for Automation and Embedded ML Register Today Date: Tuesday, April 12, 2022 Time: 9:00 am PDT | 4 pm UTC | 7:00 pm EET Duration: 23 minutes In this IoT Central MicroSession, learn how to create a non-human voice audio classification system with Edge Impulse to identify when a faucet is leaking. This demo can also be adapted for industrial use cases, such as identifying machine failures with grinding sounds, or even for wildlife conservation purposes, to recognize the vocalizations of various endangered species in the wild. Instructor: Jenny Plunkett, Senior Developer Relations Engineer, Edge Impulse Optional Hardware: Mobile Phone Preperation: Free sign-up at https://studio.edgeimpulse.com/signup Register Today

WEBINAR: Gain Insights from SAP Data with Qlik and Microsoft - 8 November 2021

 

Sponsored News from Data Science Central   Webinar: Gain Insights from SAP Data with Qlik and Microsoft Enterprises are inundated with massive amounts of SAP data and challenged to create more consumable insights without increasing headcount or system resources. It is a daunting task to deal with slow systems and manual coding to gain any value from historical data spanning thousands of products, customers, sales history, and the list goes on. In this webinar, you’ll hear how global manufacturer Greene Tweed developed an efficient, cost-effective, and logical strategy to connect Qlik Data integration and Microsoft Azure Synapse to build an intelligent supply chain for better business insight. Learn how Greene Tweed addressed their challenges and how they use data liberated from SAP for strategic analytics initiatives. In addition, you will discover: How to create a plan of attack to extract insights from massive amounts of SAP data How important change data capture is to building low latency extracts for massive data volumes Why automation with Qlik Data Integration is crucial to expedite data availability How SAP data drives insights to optimize Manufacturing & Supply Chain The gains Greene Tweed realized by moving SAP data to Azure Synapse Register Today Speakers: Matt Hayes, VP of SAP Business, Qlik David Hufnagle, Manager, Enterprise Data and Analytics, Greene Tweed Greg Vigil, Industry Solution Director – Manufacturing, Microsoft Hope to see you there, Sean Welch Data Science Central

How To Become A Task Automation Hero Using Python [With Examples] by @monterail via @Medium

Performing repetitive tasks can bore even the most resilient of us out of our minds. Lucky for us, the digital age we live in offers us a bevvy of tools to relieve ourselves of that sort of tedious labour.

I loved this and it looks incredibly useful - worth the time to investigate so that you can use it going foward.

Excel Automation Using Python Xlwings by Sandeep Burnwal via @Medium

Automation has been the buzzword for a long time and will continue to be one in the times to come. It can take many forms and this great article by Sandeep explains how you can automate Excel using Python XIwings.

A very clear and very useful thing to learn. Useful code snippets to help you get your own code right.

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.

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.

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.

Organizations gaining new benefits by automating data engineering by Jelani Harper via @infomgmt

A number of advancements have now decreased data preparation time while increasing the time available for exploration and applications.

I think there are several possible tools that enable users to do their own querying and this article talks about the one that the author is most familiar with.  Some organisations use Tableau, Pentaho or Power BI. I'm sure there are others I have not listed.

WEBINAR: Moving from BI to Automated Machine Learning - 18 October 2017

Wednesday, October 18, 2017 1:00 pm Eastern / 10:00 am Pacific 35 minutes with Q&A

Machine Learning has become a competitive differentiator in a big data world. Vast amounts of data are already overwhelming existing BI tools and analytics processes. When faced with hundreds of variables, a human's ability to efficiently identify new insights or detect changing patterns manually has also been exceeded. 

To address these challenges, BI and analytics professionals are adopting user-friendly, automated machine learning solutions.

In this webinar hosted by DataRobot, recognised analytics industry expert Jen Underwood will discuss how BI and analytics professionals can get started with automated machine learning. She will cover:

• An introduction to machine learning and popular machine learning use cases

• CRISP-DM Methodology and common algorithms (regression, clustering, classifiers, and more)

• How to get started with Automated Machine Learning 

Guest Speaker: Jen Underwood Founder, Impact Analytix

Register here

Selling data to feed hedge fund computers is one of the hottest areas of finance right now by @johndetrixhe via @qz

Kumesh Aroomoogan has come a long way from his days at Wall Street bank Citigroup, where his job was to stay on top of breaking news. He remembers getting yelled at by a trader because he stopped watching news feeds to go the bathroom and missed a market-moving headline. Now, he’s the co-founder and CEO of Accern, a company that automates his old job.

Interesting article - seems it's not only money but data that makes people wealthy.

Definition of a Quant Fund here.

An inside look at Alphabet's most ambitious AI project by Alexis C. Madrigal via @TheAtlantic

"In a corner of Alphabet's campus, there is a team working on a piece of software that may be the key to self-driving cars. No journalist has ever seen it in action until now. They call it Carcraft, after the popular game World of Warcraft." The Atlantic takes an in-depth look at how Waymo is training self-driving cars.

Interesting.  Worth reading and thinking about the way the future may be going to happen. I can't wait as long as they make sure it is safe.

Automated Data Warehouse Development

There are tools out there that enable quick Data Warehouse development.  One such tool is by  +WhereScape Data Warehousing which combines their 3D tool which helps with the planning and their RED tool which enables a supportable Data Warehouse to be built fast.  You can learn more about both products here.

+TDWI currently has a Q&A with +Mark Budzinski which talks about these products.

I think these are great but you need the knowledge of what the data is so this does not replace MDM which I think is still needed to document the data.