O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

datapine

MAY 21, 2019

“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith. Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors. The power of data analytics and business intelligence is universal.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards Slice and Dice 183

Smart Data Collective

MAY 21, 2019

Big data is redefining the future of the gaming industry. Gaming providers are using big data for a variety of purposes. These applications include the following: Getting a better understanding of customers , so they can offer better products and experiences. Protecting against security threats, which are becoming increasingly common. Adapting new payment processing solutions, such as crypto currencies.

Big Data 90

Big Data Statistics Marketing Strategy 90

IBM Big Data Hub

MAY 21, 2019

A modern data architecture (MDA) must support the next generation cognitive enterprise which is characterized by the ability to fully exploit data using exponential technologies like pervasive artificial intelligence (AI) , automation, Internet of Things (IoT) and blockchain.

Data Architecture 76

Data Architecture Internet of Things IoT Enterprise 76

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

Jet Global

MAY 21, 2019

Jet Analytics provides users with several data sources and data structures to choose from when building reports or dashboards. But how do you decide when to choose your live database, your data warehouse or your cubes? Each data source has something valuable to contribute in your reporting and analytics ecosystem, so knowing the pros and cons of when to select each one will give you a big leg up in efficiently building reports.

Reporting 75

Reporting Optimization Data Warehouse Dashboards 75

Smart Data Collective

MAY 21, 2019

. Organizations are using big data to solve many of their most pressing challenges. Some big data applications have received considerably more attention than others. Marketing and finance are two of the functions that are most dependent on big data. However, there are other benefits of big data that are just as important but receive far less publicity.

Big Data 75

Big Data Cost-Benefit Predictive Analytics Insurance 75

Dataiku

MAY 21, 2019

If this month’s Google I/O conference is any indication , then incorporating machine learning (and deep learning) into existing products and processes to make them more efficient or useful is the future. From healthcare to sales , deep learning has wide applications; and with last week’s launch of Hailo ’s newest deep learning chip, they will only get wider.

Deep Learning 74

Deep Learning Machine Learning Sales Data Science 74

IBM Big Data Hub

MAY 21, 2019

There is no AI without data. That’s why we’ve put together a prescriptive set of five steps we call the ladder to AI to help our enterprise clients get their data ready. The journey of the AI ladder starts with collecting the data you need to build models, followed by organizing your data so you can find and safeguard it. The next two steps in the ladder are analyzing your data to better understand their business and know where to apply AI -- and finally, infusing AI inside of your processes wit

Enterprise 73

Enterprise Modeling IT 73

Teradata

MAY 21, 2019

Chad Meley explains how the concept of compound interest can be applied to your data and analytics investment strategy.

Data Analytics 89

Data Analytics Analytics Strategy 89

Data Virtualization

MAY 21, 2019

The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. are found coexisting with relational databases to fuel the.

Data Warehouse 45

Data Warehouse Data Lake IoT Data Governance 45

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

Hurwitz & Associates

MAY 21, 2019

By Jean S. Bozman . Red Hat’s Enterprise Linux (RHEL) distribution and Red Hat OpenShift have become a foundation for Red Hat’s growth into a $3.4 billion software company. The latest releases – the RHEL 8 operating environment and Red Hat OpenShift 4 container platform – clearly target the current wave of cloud migration that is focused on creating multi-cloud computing environments.

Software 40

Software Enterprise Machine Learning Management 40

CDW Research Hub

MAY 21, 2019

Sirius is honored to announce that we have been named Nutanix ’s 2019 Global Partner of the Year. This exclusive recognition was presented earlier this month during the.NEXT Conference in Anaheim, CA, and acknowledges the strength and success of our partnership with Nutanix. This prestigious selection is the culmination of our relentless focus on our clients’ business outcomes, working with them to fully optimize their IT environments.

Optimization 40

Optimization Software Strategy IT 40

The Data School

MAY 21, 2019

Column oriented databases have become dominant over row oriented databases in data warehousing

Modeling 40

Modeling 40

Smart Data Collective

MAY 21, 2019

Big data and e-commerce have been carefully interwoven for years. Businesses with an online presence have looked to big data to provide better customer service. Some examples of this include: Monitoring user engagement to see how customers behave online. Developing more effective graphic designs with the assistance of artificial intelligence. Ensuring the website operates as smoothly as possible.

Big Data 97

Big Data Interactive Manufacturing Predictive Analytics 97

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

bridgei2i

MAY 21, 2019

The financial industry is undergoing a radical shift that’s being driven by mounting regulation and compliance pressures, changing business models, new competition from FinTechs, and disruptive technologies. Introducing innovative technologies such as Artificial Intelligence(AI) can help the financial sector to automate various processes, manage financial advisory services, and reduce the cost of various business expenses.

Unstructured Data 40

Unstructured Data Sales Data-driven Finance 40

Smarten

MAY 21, 2019

The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, nor does the process stop with training. In order to get business users to embrace and adopt self-serve augmented data discovery tools, the enterprise must approach the implementation with appropriate change management processes.

Analytics 40

Analytics Data-driven Metrics Enterprise 40