Wed.May 01, 2019

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Use Collaboration to Maximize the Value of Your Analytics

David Menninger's Analyst Perspectives

About 10 years ago, social media tools like Facebook, Twitter and LinkedIn introduced a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input.

Analytics 137
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It’s Spring: Time To Dust Off Forrester’s Blockchain Predictions

Martha Bennett

More than six months have passed since I wrote Forrester’s predictions 2019 report for distributed ledger technology (DLT, AKA blockchain). In the blockchain world, that’s ages ago. As I keep being asked how those predictions are shaping up, and having just attended two excellent events in New York, now’s a good time to take stock. […].

Reporting 110
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Highlights from the Strata Data Conference in London 2019

O'Reilly on Data

Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more. People from across the data world are coming together in London for the Strata Data Conference. Below you'll find links to highlights from the event. Making the future. James Burke asks if we can use data and predictive analytics to take the guesswork out of prediction.

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Interview with Faraz Shafiq

Corinium

AI will allow us to meet a cause that was defined 15 years ago but it has its challenges, says Faraz Shafiq, SVP and CAIO of Cambia Health Solutions.

IT 150
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

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.

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Sustaining machine learning in the enterprise

O'Reilly on Data

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise.

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5 ways IBM Cognos Analytics is transforming business

CIO Business Intelligence

With business generating more data than ever before, organizations are rapidly investing in business intelligence (BI) capabilities to help them generate insights from that data to drive better business decisions and identify new opportunities.

Analytics 107

More Trending

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What Is the Biggest Challenge Facing CMOs Today? Building, Measuring, and Maintaining Brand Equity.

Teradata

Teradata CMO Martyn Etherington discusses how brands can build, measure, and maintain brand equity. He also explains why customer experience is critical to a brand's success.

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Finding your North Star

O'Reilly on Data

Cait O’Riordan discusses the North Star metric the Financial Times uses across the organization to drive subscriber growth. Continue reading Finding your North Star.

Metrics 111
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Is Big Data Necessary For Creating A Successful Online Business?

Smart Data Collective

The internet makes it easier for small entrepreneurs to succeed. When you try to create a business online, you don’t need to have technical experience. In fact, you don’t need to know much about website building or programming at all this can easily be handled by using countless tools that are available online. However, there are still some competencies that you need to develop.

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Making data science useful

O'Reilly on Data

Cassie Kozyrkov explains how organizations can extract more value from their data. Continue reading Making data science useful.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

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.

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Healthcare Analytics from the Pros

Dataiku

Medicine is always evolving, but healthcare as an industry struggles to incorporate data analytics into their workflows. We sat down with a crew of expert researchers, data scientists, and clinicians with a plethora of applications for how analytics and machine learning can help doctors, nurses, technicians, and patients have better experiences and outcomes.

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Making the future

O'Reilly on Data

James Burke asks if we can use data and predictive analytics to take the guesswork out of prediction. Continue reading Making the future.

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Addressing Irreproducibility in the Wild

Domino Data Lab

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University. Special thanks to Mawer for the permission to excerpt the slides in this Domino Data Science Field Note.

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Using Technology to Reduce Operating Costs in Insurance

Decision Management Solutions

In February, we published a blog post on “Using Technology to Add Value in Insurance”. That post, referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question? , in which he states that there are only three levers of value in insurance: 1. Sell More , 2. Manage Risk Better , and 3. Cost Less to Operate.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

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.

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Investing or Focusing on AI Does Not Alone Assure Success

Andrew White

Two articles in today’s US print edition of the Financial Times highlight the simultaneous offer of promise and peril that AI brings. One article describes the meteoric rise of a start-up; the other the failure of another. In ‘ Robotics start-up Anki reaches end of the road ’ we here of a small firm laying off all its workers today after failing to negotiate new investor support.

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Owens-Illinois plans for the future after a successful migration to IBM Db2

IBM Big Data Hub

Owens-Illinois (O-I), the world’s largest manufacturer of glass containers, recently undertook a global migration from Oracle to Db2. Learn more about the migration and its success from O-I executives.

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It’s Spring: Time To Dust Off Forrester’s Blockchain Predictions

Martha Bennett

More than six months have passed since I wrote Forrester’s predictions 2019 report for distributed ledger technology (DLT, AKA blockchain). In the blockchain world, that’s ages ago. As I keep being asked how those predictions are shaping up, and having just attended two excellent events in New York, now’s a good time to take stock. […].

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Make your own Super Pandas using Multiproc

MLWhiz

Parallelization is awesome. We data scientists have got laptops with quad-core, octa-core, turbo-boost. We work with servers with even more cores and computing power. But do we really utilize the raw power we have at hand? Instead, we wait for time taking processes to finish. Sometimes for hours, when urgent deliverables are at hand. Can we do better?

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How to Build an Experimentation Culture for Data-Driven Product Development

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

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April 2019 Blog Post Round-Up

CDW Research Hub

Links to last month’s most popular posts: Managing Third-Party Risk: Lessons from the Field. 6 Stages to the Analytics-Driven Security Journey. Case Study & White Paper: Health System Sets the Stage for Transformation with Blockchain Technology. 4 Tips to Maximize Your IAM Strategy in the Cloud. The post April 2019 Blog Post Round-Up appeared first on Sirius Computer Solutions.

Risk 40