O'Reilly on Data
JANUARY 22, 2019
An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. In this blog post, we explore three types of errors inherent in all financial models, with a simple example of a model in TensorFlow Probability (TFP).
IBM Big Data Hub
JANUARY 22, 2019
The Forrester Wave has named IBM a leader across five AI-related categories. Most recently, IBM Cloud Private for Data earned its place among vendors offering enterprise insights platforms.
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Paul DeBeasi
JANUARY 25, 2019
Developers with no data science experience are now able to integrate Machine Learning (ML) with IoT. As the number of IoT endpoints proliferate, the need for organizations to understand how to architect machine learning with IoT will grow rapidly. However, for this to occur, IoT architects and data scientists must overcome the challenge of having two very different disciplines collaborate closely to design an ML-powered IoT system.
BizAcuity
JANUARY 25, 2019
Today, there is a vast ocean of data that is being amassed every minute, every day. The biggest challenge is what we make of that data and how fast. Real-time analytics is a practice that analyzes this data as and when it comes into the system. Analysts are continuously sifting through and studying this data in order to identify a pattern or identify important insights that help can help businesses make informed decisions.
Speaker: John Mansour
If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.
erwin
JANUARY 24, 2019
Organizations are responsible for governing more data than ever before, making a strong automation framework a necessity. But what exactly is an automation framework and why does it matter? In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape.
IBM Big Data Hub
JANUARY 23, 2019
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.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
BizAcuity
JANUARY 21, 2019
Technology is the pursuit for more, isn’t it? Today, across all spectrums of business, technology is being used to empower smarter and efficient solutions. At BizAcuity, we’ve identified one such domain of business that we felt could use a technological makeover. And that is what today’s blog is about – Customer Behaviour Analysis.
Domino Data Lab
JANUARY 24, 2019
Reflections. Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. This post describes our observations about these three segments and offers advice for folks evaluating products in this space.
IBM Big Data Hub
JANUARY 24, 2019
A new Forrester Consulting study commissioned by IBM from October 2018 shows that fast data with fast analytics is an enormous, rapidly growing resource that’s not being used to its full potential.
Timo Elliott
JANUARY 22, 2019
Andy Bitterer and Timo Elliott talking about the top ten analytic trends for 2019. The first #AskSAP web seminar of the year was on the topic of the top trends in analytics for 2019. It was hosted by Avery Horzewski and featured SAP Analytic Evangelist Andy Bitterer and myself chatting about our top ten favorite themes for this year in the area of business intelligence, analytics, data platforms, big data, and artificial intelligence.
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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?
DataRobot Blog
JANUARY 20, 2019
by Jen Underwood. A long time has passed since I’ve last written. Thank you to my peers that have reached out and asked what’s going on. Rapidly growing DataRobot keeps me extremely busy. Read More.
Domino Data Lab
JANUARY 20, 2019
This Domino Data Science Field Note provides very distilled insights and excerpts from Been Kim ’s recent MLConf 2018 talk and research about Testing with Concept Activation Vectors (TCAV), an interpretability method that allows researchers to understand and quantitatively measure the high-level concepts their neural network models are using for prediction, “ even if the concept was not part of the training “ If interested in additional insights not provided in this blog post, please refe
IBM Big Data Hub
JANUARY 21, 2019
If you’re an IT professional managing data, it’s time to start planning for the California Consumer Privacy Act of 2018, also known as CCPA. The new guidelines will go into effect on January 1, 2020.
Teradata
JANUARY 21, 2019
Applying deep reinforcement learning to real world problems has the potential to revolutionize how businesses tackle many of their core business challenges.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
ScienceSoft
JANUARY 24, 2019
Is inventory optimization still your headache? Here, we describe three pills you can take - simple math, statistics and machine or namely deep learning - and show why data science can be your #1 painkiller.
Data Virtualization
JANUARY 23, 2019
Mergers and acquisitions are a fact of life, and they often take a toll on everyday business; people, real estate, processes, and systems need to be properly integrated before the acquiring company and the acquired company can act as one. The post How Digital Realty Weathers Acquisitions with No Impact on Daily Operations appeared first on Data Virtualization and Modern Data Management.
IBM Big Data Hub
JANUARY 21, 2019
Every company has its own set of problems that it attempts to solve. In our case, we needed a more efficient and accurate way to identify the relationships between businesses on which we maintain data.
Smarten
JANUARY 22, 2019
A Data and Analytics Platform to Support Business Users and Data Scientists! A cutting-edge advanced analytics vendor takes an innovative approach to the data and analytics platform by focusing on Technology Leadership, Team Environment and a Customer and Partner Focus. A modern analytics platform should include predictive analytics for business users with cutting-edge business intelligence and data discovery tools.
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.
Paris Technologies
JANUARY 22, 2019
With the next big release of PowerOLAP® Version 20 expected for Q3, now is the best time to upgrade to Version 18, if you haven’t already done so. For one, the transition to Version 20 will be that much easier. And, right now, you can take advantage of some great features in advance of Version 20’s official release. The two biggest highlights of this Version 18 upgrade are the new Initiators and […].
Teradata
JANUARY 21, 2019
Applying deep reinforcement learning to real world problems has the potential to revolutionize how businesses tackle many of their core business challenges.
Nutanix
JANUARY 21, 2019
In Part I of this blog, we talked about “the interesting times we live in” regarding the state of Federal IT. The problem is – managing and delivering IT shouldn’t be an adventure.
Smarten
JANUARY 21, 2019
Learning for Citizen Data Scientists and Data Literacy Across the Enterprise! So you want to transform your business users and encourage learning for Citizen Data Scientists to enable data literacy across your enterprise? If your business is like most, your average business user doesn’t know (or need to know) the details of sophisticated algorithms and analytical techniques.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Timo Elliott
JANUARY 22, 2019
2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. 1. Machine learning everywhere. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.
Teradata
JANUARY 23, 2019
Ron Luebke discusses the pains of switching cloud providers.
Nutanix
JANUARY 24, 2019
We recently concluded a whirlwind three days at the National Retail Federation (NRF) conference in New York, where we had great conversations with retailers and suppliers of all types.
Business Over Broadway
JANUARY 20, 2019
Analysis of usage patterns of 16 data science programming languages by over 18,000 data professionals showed that programming languages can be grouped into a smaller set (specifically, 5 groupings). That is, some programming languages tend to be used together apart from other programming languages. A few of the different groupings of languages reflect specific types of applications or specific roles that data professionals could support, including analytics, general-purpose, and front-end effort
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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.
Timo Elliott
JANUARY 23, 2019
I was honored yesterday to be one of the panelists in one of a series of SAP Radio 2019 prediction shows, hosted by Bonnie D. Graham. You can catch a recording of the session Voice America site or below. . [link]. I’m on at 21′ in — here’s a rough transcript of what I talked about: “My prediction for 2019 is that we’re at the start of a new golden age for human intelligence. .
Teradata
JANUARY 23, 2019
Ron Luebke discusses the pains of switching cloud providers.
Nutanix
JANUARY 24, 2019
Cloud cost anomaly detection is a vital tool in keeping your cloud costs under control. To put it in perspective, balancing your own budget isn’t always easy – even if you’re the most frugal person you know.
Cloudera
JANUARY 22, 2019
Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.
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