KDnuggets

SEPTEMBER 17, 2019

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

Data Science 123

Data Science Deep Learning Statistics Machine Learning 123

TDAN

SEPTEMBER 17, 2019

There is a movement to upend traditional thinking about information systems by putting data and meaning at the center of strategy, architecture, and system development sequencing. It is the most recent of a series of data-centric waves which, over several decades, have attempted to remedy the entrenched application-centric paradigm. Past waves have receded, largely because […].

Strategy 82

Strategy Data Architecture IT Data Strategy 82

KDnuggets

SEPTEMBER 17, 2019

Lately, varying improvements over BERT have been shown — and here I will contrast the main similarities and differences so you can choose which one to use in your research or application.

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122

TDAN

SEPTEMBER 17, 2019

I am surprised to see a lot of people jumping straight into logical or even physical modeling and skipping conceptual modeling. Don’t they understand the value of conceptual modeling? Don’t they understand the difference between the various levels of modeling? Or do they have cognitive limitations? In this column, I will elaborate on the importance […].

Modeling 81

Modeling Data Architecture Data Strategy Strategy 81

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation

KDnuggets

SEPTEMBER 17, 2019

The article contains a brief introduction of Bioinformatics and how a machine learning classification algorithm can be used to classify the type of cancer in each patient by their gene expressions.

Machine Learning 121

Machine Learning 121

TDAN

SEPTEMBER 17, 2019

There have been a couple of different things converged in my media feeds that highlight a key issue that all data management professionals and leaders in information management need to be conscious of – Group Think. This manifests itself in at least two ways in the following examples I’ll use to illustrate my points. Each […].

Management 80

Management Risk Management Risk Data Governance 80

Jet Global

SEPTEMBER 17, 2019

Directions EMEA is the biggest autumn event for Microsoft Partners and this year’s show is set to be bigger than ever – with 2,200 attendees from Partners and ISV companies meeting in Vienna, Austria October 9th – 11th. A true “Who’s Who” of the Microsoft Partner channel will be at this event, and we are excited to be there again this year, now as insightsoftware and Jet Global together!

Data Processing 80

Data Processing Reporting Management Strategy 80

KDnuggets

SEPTEMBER 17, 2019

What other creative tools for data science beyond Python and R can you use to make an impression? It's not about the tool -- it's about its impact.

Data Science 91

Data Science IT Visualization 91

TDAN

SEPTEMBER 17, 2019

In my last article I suggested that many organizations have approached Data Governance incorrectly using only centralize data governance teams and that approach is not working for many. Large organizations generally need a decentralized approach, to engage resources in all functional units (my definition of “a village”) to Operationalize data governance across many functional business […].

Data Governance 76

Data Governance Metadata Data Strategy Strategy 76

Smart Data Collective

SEPTEMBER 17, 2019

Machine learning is creating pivotal change in the energy industry. Towards Data Science wrote about the changes that machine learning is bringing to this field. They pointed out that Bill Gates wrote a letter in 2017 to graduate students across the country, which stated that machine learning is going to be the biggest disruptor in this industry. You need to consider the benefits of using an electrical system that relies on machine learning technology.

Machine Learning 71

Machine Learning Enterprise Insurance Cost-Benefit 71

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Strategy

KDnuggets

SEPTEMBER 17, 2019

Join this technical webinar on Oct 3, where Domino Chief Data Scientist Josh Poduska will dive into popular open source and proprietary AutoML tools, and walk through hands-on examples of how to install and use these tools, so you can start using these technologies in your work right away.

Data Science 67

Data Science Technology 67

TDAN

SEPTEMBER 17, 2019

Did you know that 90% of all data has been generated over the last 2 years? Big Data has been an important topic in the marketing scene for quite some time. It has been a major challenge for Chief Marketing Officers (CMOs) because it’s not easy to organize and extract useful insights from massive amounts of […].

Big Data 68

Big Data Marketing Data Architecture IT 68

IBM Big Data Hub

SEPTEMBER 17, 2019

The IBM DataOps methodology and practice focuses on bringing agility, speed, and scale to analytics through automation, data quality and governance.

Data Quality 65

Data Quality Analytics 65

Smarten

SEPTEMBER 17, 2019

Is Augmented Data Discovery Easy Enough for My Business Users? A data discovery tool is a crucial tool for every business user in your organization. With so many sources of data, in so many locations with your enterprise, it is impossible for users to know whether they have access to complete, accurate data to make decisions. With the right Advanced Analytics Tools , business users can have access to data integrated from disparate data sources and can use that date for Advanced Data Discovery so

Predictive Analytics 51

Predictive Analytics Forecasting Visualization Data Integration 51

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Testing

DataCamp

SEPTEMBER 17, 2019

DataCamp is the only interactive learning platform designed to prepare your team to better understand the most powerful asset your organization has—data.

Data-driven 52

Data-driven Interactive 52

Teradata

SEPTEMBER 17, 2019

Learn how to better classify data & analytics within the analytic ecosystem by analyzing the various states of data & analytics within organizations. Read more.

Analytics 45

Analytics Data Analytics 45

TDAN

SEPTEMBER 17, 2019

Some industry experts say that just a couple of years ago, cloud computing was dismissed as the latest technology trend, which was good for generating a lot of noise. Right now, it is safe to conclude that techies and non-techies alike have already heard of Cloud Computing and its benefits such as cost savings, increased […].

Cost-Benefit 40

Cost-Benefit Technology IT Data Architecture 40

Peter James Thomas

SEPTEMBER 17, 2019

Today we launch a new on-line resource, The Data Strategy Hub. This presents some of the most popular Data Strategy articles on this site and will expand in coming weeks to also include links to articles and other resources pertaining to Data Strategy from around the Internet. If you have an article you have written, or one that you read and found helpful, please post a link in a comment here or in the actual Data Strategy Hub and I will consider adding it to the list.

Data Strategy 40

Data Strategy Strategy Analytics IT 40

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Management

DataRobot

SEPTEMBER 17, 2019

Today, we announced that we have raised $206M in Series E financing. This new capital will significantly accelerate our ability to execute on our vision of helping all organizations become AI-driven. I want to briefly summarize why we raised this additional capital and how we plan to execute on this vision.

Finance 15

Finance 15

Smart Data Collective

SEPTEMBER 17, 2019

AI barely played a role in the beginning of online search engines. The earliest search engines accepted payments from companies that wanted to be at the top of the listings. However, AI is becoming more important than ever. Google is using AI to assign SERPs more than ever. Savvy SEO strategists are also using AI too. AI is also important in local SEO, because businesses need to know how to automate essential functions and identify approaches that get the best results.

Strategy 63

Strategy Technology Marketing Optimization 63

Jet Global

SEPTEMBER 17, 2019

Are you ready to maximize the performance of your Microsoft Dynamics solution? Whether you are interested in personal development or larger organizational goals, the 2019 User Group Summit North America has the training and networking you are looking for. As the largest in-person event for users of Microsoft’s business process management platforms such as Microsoft Dynamics 365 Business Central, 365 for Finance and Operations, NAV, GP, and AX – User Group Summit provides hands-on learning

Finance 53

Finance Dashboards Reporting Data Lake 53

Birst BI

SEPTEMBER 17, 2019

Data visualization tools, desktop data discovery tools, and visual analytics are examples of traditional self-service BI tools that business analysts embrace because they provide a user-friendly way of quickly turning data into insights. These tools are geared toward business analysts that have the skills and knowledge to acquire the right data sets, perform the analysis, and present the insights needed to solve a business problem.

Visualization 45

Visualization Risk Reporting Enterprise 45

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Data-driven

Depict Data Studio

SEPTEMBER 17, 2019

In my sixth year of self-employment, the demand for data visualization skills is stronger than ever. Are you ready to take your organization’s data communications skills to the next level? The once-a-year enrollment period is now open for Great Graphs: Transform Spreadsheets into Stories. This online training program includes a mix of synchronous and asynchronous learning.

Visualization 40

Visualization Consulting Dashboards Reporting 40

Smarten

SEPTEMBER 17, 2019

The Smarten suite of advanced analytics tools is now available for a free 30-day trial on the AWS Marketplace. This augmented analytics solution includes smart data visualization, assisted predictive modeling and a self-serve data preparation assisted by machine learning to help business users without any data science skills to create, use and share predictive models on their own.

Analytics 51

Analytics Predictive Modeling Reporting Machine Learning 51