MassMutual Taps Into the Power of Data Science

Data Breach Today

Ariel Weintraub on Putting Data to Work in the SOC and IAM Ariel Weintraub joined MassMutual last fall to focus on putting data science to work to help improve the insurance company's security operations and identity and access management programs.

Data Science Virtual Expert Panel Presented by AWS

Perficient Data & Analytics

AWS will feature one of our experts to speak on a panel about the evolution and progress being made to solve critical business problems such as customer personalization and forecasting through the use of data science. Leveraging Innovations in Data Science.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Women on the rise in Data Science

IBM Big Data Hub

IBM Data Science and AI Elite team members Mehrnoosh Vahdat and Rachael Dottle were just one month into their IBM careers when they received their first assignment last July. . Their mission was to generate a proof of concept designed to enhance the value of data science and inject the results into workflows for business users and clients.

MicroServices: Today’s data science gold rush

Thales eSecurity

1 For more on microservices check out two of my earlier blogs, “ Securing Microservices ,” and “ Seven Microservices Identity Questions to Secure your Data. ”. It’s the next data science gold rush! Data security

Data science: Breaking down the silos

IBM Big Data Hub

Today’s data science and analytics teams are often composed of individuals with a variety of skill sets, educational backgrounds, levels of exposure to open source tools and professional needs. Here’s a typical breakdown

Best practices for building a data science dream team

Information Management Resources

An effective data science team must include people with overlapping skills, all with a deep understanding of a project’s overall vision. Data Scientist Career advancement Data science

17 top data science and machine learning platforms

Information Management Resources

RapidMiner, TIBCO Software, SAS and KNIME are among the leading providers of data science and machine learning products, according to the latest Gartner Magic Quadrant report. Data science Machine learning Artificial intelligence

Quick Tips on How to Sell Your Data Science Model

Perficient Data & Analytics

During a five-week IBM training program, I learned a few things about how to sell data science models that I’d like to share it with you. Drew Conway’s Data Science Venn Diagram. The combination of these skills are what makes a good data scientist.

How Kubernetes marries IT and data science roles

Information Management Resources

Using Kubernetes as a common orchestration layer empowers IT to create self service environments for data scientists. Artificial intelligence Machine learning Data management Data science

Keep the train rolling: partner momentum in the data science market

IBM Big Data Hub

How has the newer data science technology such as Watson Studio, Watson Machine Learning and Watson OpenScale been picked up by the business partner community? The new data science technology has been very well received by our partner community.

When faster data science moves the world

IBM Big Data Hub

Learn how the IBM Integrated Analytics System, a unified data platform built on the IBM Common SQL Engine, helps do data science faster with high performance, embedded machine learning capabilities and built-in tools for data scientists to deliver analytics critical to increasing your organization’s competitiveness

Data Science: Influencers review 2018 and share their 2019 predictions

IBM Big Data Hub

Data science was one of the hot topics of 2018, and it’s likely to dominate again in 2019. We've asked five key data science influencers to take a look back at 2018 and look ahead at what's to come in 2019

Data science transformations: Learn from these clients at Think 2019

IBM Big Data Hub

If you’re a data scientist or leading a team, Think 2019 is where you’ll want to be in February to hear success stories from clients using IBM’s data science portfolio of solutions

What is the impact of data science automation?

IBM Big Data Hub

As a result, data scientists can be liberated to commit more time to designing, testing and deploying machine learning models. To learn more about what these developments mean for the data science community, I sat down with IBM’s Vice President of AI, IBM Research, to get his perspective.

IBM and Anaconda partner to accelerate AI innovation with the power of open source data science

IBM Big Data Hub

The data science market is evolving rapidly. Many data scientists and developers today want to make use of the latest open source innovations during these steps. Therefore, I’m excited to share that IBM and Anaconda are joining forces under an OEM agreement to simplify the deployment of data science projects across any cloud Businesses need to respond to a volatile climate and be able to scale cost-efficiently by automating AI lifecycle management.

Ten expert tips for visual data science

IBM Big Data Hub

Data science and machine learning provide the basis for business growth, cost and risk reduction and even new business model creation -- but implementing predictive analytics does present some challenges. IT Central Station members have shared tips that help organizations overcome the challenges in effective data preparation, model development and training

Transforming business with data science partners, open source and IBM innovation

IBM Big Data Hub

Recently, I sat down with Kyle Weeks, Program Director for Ecosystems in Data Science and AI. I wanted to review some exciting new opportunities made possible by several recent developments in IBM Data Science

Experts answer your top data science and machine learning questions

IBM Big Data Hub

There’s no doubt data science and machine learning are main areas of focus for enterprises to better their business. However, talking about data science and machine learning isn’t the same as making it a reality

Win with AI: John Thomas of IBM on putting skin in the data science game

IBM Big Data Hub

John Thomas, IBM distinguished engineer and director of analytics, talks with Dave Vellante in NYC ahead of the recent “Change the Game: Winning with AI event in NYC” to talk about how the IBM Data Science Elite team offers data science expertise as a service to a variety of clients to a variety of organizations, cutting across multiple industries.

How the Data Science Elite helped uncover a gold mine at Experian

IBM Big Data Hub

Find out more about how the IBM Data Science Elite team helped Experian succeed at better analyzing their data at Think 2019

IBM’s Data Science and AI Elite helps Geisinger break new ground in sepsis care

IBM Big Data Hub

Learn how Geisinger Health System tapped the IBM Data Science and AI Elite team to reduce mortality from sepsis

4 operating models to consider when setting up a data science team

Information Management Resources

‘Technology drives business’ is very much applicable to the case of how data science is being evaluated for adoption by many enterprises. Data modeling Data management Data science

How Data Science Experience improves accuracy for the insurance industry

IBM Big Data Hub

In this Q&A, IBM financial services solution architect Irina Saburova discusses an insurance use case with IBM Data Science Marketing Lead Rosie Pongracz. In this scenario common to the insurance industry, an organization needs to adjust its operations based on upcoming weather event and multiple weather indicators can improve forecast accuracy

6 Steps for Applying Data Science to Security

Dark Reading

Two experts share their data science know-how in a tutorial focusing on internal DNS query analysis

Get an IBM data science professional certificate on Coursera

IBM Big Data Hub

The swelling demand for data scientists coupled with the evident skills gap has implications for the global economy as well as the tech industry. What’s causing it, and what can be done to address it

5 cool vendors in data science and machine learning

Information Management Resources

Data science Machine learning Data ScientistDimensionalMechanics, Immuta and Octopai are among the leading vendors in the machine learning space, according to a new report from Gartner.

16 top platforms for data science and machine learning

Information Management Resources

Machine learning Data science Data managementAlteryx, KNIME and SAS are among the top vendors in this space, according to a new Magic Quadrant report from Gartner.

What 15 top data science and analytics jobs are earning

Information Management Resources

According to the compensation website payscale.com, as of April 29, 2018, nearly half of top data science, data analytics and machine learning jobs were earning under $100,000 nationally. Data Scientist Data Analyst Data science

Deliver a customer experience fit for royalty with data science and AI

IBM Big Data Hub

Learn what you can deliver with data science and AI Delivering a great customer experience is more important than ever.

Top trends to expect in cloud computing, data science and AI

Information Management Resources

Artificial intelligence Data science Cloud computingLast year could be referred to as the year of the cloud. In 2020, however, cloud deployments will become more popular as organizations look to reap the benefits of hybrid-cloud models.

Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists ? Harvard Data Science Review

Information Governance Perspectives

via Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists · Harvard Data Science Review Abstract There is increasing recognition that the data scientist ‘unicorn’—one who can master all the necessary skills of data science required by businesses—exists only rarely, if at all. Successful data science teams in business organizations, then, need to assemble people Continue reading

New book provides an accessible and practical introduction to data science

CILIP

New book provides an accessible and practical introduction to data science. Facet Publishing announce the publication of Practical Data Science for Information Professionals by David Stuart.

Revelwood helps marketers hit the bullseye with cloud-based data science

IBM Big Data Hub

Machine learning has the potential to make the lives of marketers easier, but few marketing teams currently have the in-house data science skills they need to take advantage of it

Field of Data Science in 2018

Perficient Data & Analytics

It is no secret that a data science and analytics specialty was one of the hottest and fastest growing careers in 2017, leading to resource shortages (as denoted by the picture below). However, in 2018 and beyond, a data scientist will evolve into data engineer, a data steward, and a governance lead. Every field will groom their own data scientists including finance, marketing, sales, HR, procurement, risk, compensation, and even database administration.

When Morpheus met Watson: JPMC teams with IBM Data Science and AI Elite

IBM Big Data Hub

Learn how the IBM Data Science and AI Elite Team helped JPMorgan Chase with AI initiatives

3 challenges facing insurers in data science implementation

Information Management Resources

Data mastery is a priority for carriers across business lines, but there are still roadblocks. Data science Data Scientist Chief Data Officer Data warehouses

IoT Anomaly Detection 101: Data Science to Predict the Unexpected

Dark Reading

You can predict the chance of a mechanical failure or security breach before it happens. Part one of a two-part series

Data Science for All: What is it? Why care? How do I get it?

IBM Big Data Hub

Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the data science journey, IBM created the Data Science for All webcast

What is the Future for Data Science Platforms?

Perficient Data & Analytics

What will the future holds for Data Science and Machine Learning platforms? Most of you already saw the Gartner’s perspective on the evolution of Data Science that was released at the beginning of 2018 and familiar with the outcome. I will be honest with you, I was a little surprised myself, and probably you were too, with the results for the leaders in Data Science and Machine Learning field; I expected to see Microsoft, Google, or IBM.

Will data science, machine learning and AI ‘save’ IT security?

Information Management Resources

The importance of identifying data sources, collecting those sources, and applying them wisely is key to prevention, the reduction of threat actor dwell time, and threat mitigation. Data security Artificial intelligence Machine learning Data science Cyber security