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Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. Profiles of IT executives suggest that many are planning to spend significantly in cloud computing and AI over the next year. This concurs with survey results we plan to release over the next few months. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions.
I am happy to share some insights about IBM drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.
The profile of a data scientist is changing slightly as the profession becomes more solidified. Data Science 365 conducts a study to determine some of the characteristics of a “typical data scientist.” The below infographic covers a wealth of information from programming languages used to educational backgrounds to locations. It is definitely worth looking at to understand the attributes of a data scientist in 2019.
The focus on customer needs for greater choice and flexibility is a constant at the IBM Think 2019 conference. Nowhere is this more evident than in IBM Hybrid Data Management, which supports data of any type, source and structure, be it on-premises or in the cloud.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
The O’Reilly Data Show Podcast: Siwei Lyu on machine learning for digital media forensics and image synthesis. In this episode of the Data Show , I spoke with Siwei Lyu , associate professor of computer science at the University at Albany, State University of New York. Lyu is a leading expert in digital media forensics, a field of research into tools and techniques for analyzing the authenticity of media files.
I am happy to share some insights on Infor based on our latest market Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.
The field of data science is moving fast. People are claiming to be data scientists; yet the knowledge, experience, and backgrounds of those people can be very different. Different is not bad. However, there a little standards around what exactly a data scientist is. Sticking with this week’s theme of “What is a Data Scientist”, an organization titled, Initiative for Analytics and Data Science Standards (IADSS) has kicked-off a research study at global scale.
The field of data science is moving fast. People are claiming to be data scientists; yet the knowledge, experience, and backgrounds of those people can be very different. Different is not bad. However, there a little standards around what exactly a data scientist is. Sticking with this week’s theme of “What is a Data Scientist”, an organization titled, Initiative for Analytics and Data Science Standards (IADSS) has kicked-off a research study at global scale.
IBM General Manager for Data and AI Rob Thomas has said organizations can't have effective AI without sound IA (Information Architecture). And one of the pillars of any IA is data management.
The rate at which organizations have adopted data-driven strategies means there are a wealth of digital transformation examples for organizations to draw from. By now, you probably recognize this recurring pattern in the discussions about digital transformation: An industry set in its ways slowly moves toward using information technology to create efficiencies, automate processes or help identify new customer or product opportunities.
State-of-the-art pre-training for natural language processing with BERT Javed Qadrud-Din was an Insight Fellow in Fall 2017. He is currently a machine learning engineer at Casetext where he works on natural language processing for the legal industry. Prior to Insight, he was at IBM Watson. In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing.
Sales Analytics in simple terms can be defined as the process used to identify, understand, predict and model sales trends and sales results and in this process of understanding of these trends helps its users in finding improvement points. Sales Analytics is used to determine the success of the previous sales drive and forecast in addition to determine how future sales will fare.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
During the IBM flagship Think conference in San Francisco today, businesses looking to accelerate their transformation with the IBM AI Watson were treated to news that they’ll be able to build, deploy and run AI models and applications across any cloud, giving them the freedom to apply Watson capabilities to their data wherever it is stored.
by Jen Underwood. In the spirit of Valentine’s Day, let’s explore a fun little Relationship App quiz that forecasts how long your relationship will last. Data from a Stanford University study, How Couples. Read More.
Dating apps are changing the ways we meet new romantic partners. Whether you’ve succumbed begrudgingly or gleefully, millennials on average spend 10 hours a week swiping and chatting on online dating apps. We know that recommendation engines are keen to predict relationships and anticipate breakups , so that they can send you ads for spa days and ice cream.
Lukas Biewald is the founder of Weights & Biases. He was previously the founder of Figure Eight (formerly CrowdFlower). This blog post provides insights into why machine learning teams have challenges with managing machine learning projects. He also provides best practices on how to address these challenges. This post was provided courtesy of Lukas and originally appeared on Medium.
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Today at Think 2019, IBM announced a new vision for the future of AI and digital transformation. Along the way, we made a number of announcements and updates that could profoundly impact how enterprises will use analytics and AI to shape the future of their business. In all, it was definitely a big day of news for IBM partners and clients. In case you missed it, here are three major announcements for analytics pros from Think 2019.
Today we are proud to announce our support for ADLS Gen2 as it enters general availability on Microsoft Azure. CDH 6.1 already includes support for MapReduce and Spark jobs, Hive and Impala queries, and Oozie workflows on ADLS Gen2. The Cloudera platform delivers a one-stop shop that allows you to store any kind of data, process and analyze it in many different ways in a single environment, and integrate with the rest of your data infrastructure.
We do a lot of decision management projects, helping clients adopt the technologies and approaches they need to succeed with digital decisioning and decision automation. One of the key technologies for these types of projects is a Business Rules Management System (BRMS). Sometimes, we get push-back on using business rules because existing business rules projects or past business rules experience have soured a company’s perception of the effectiveness of the technology.
When I hear or read that artificial intelligence (AI) is “disrupting” financial planning and analysis, I tend to challenge the premise. The word “disrupt” means to me to interrupt, alter or destroy the structure of something. I look at AI (or really all technology for that matter) as having the potential to enhance and/or improve the FP&A function.
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
Few data-driven technologies provide greater opportunity to derive value from Internet of Things (IoT) initiatives as machine learning. The accelerated growth of data captured from the sensors in IoT solutions and the growth of machine learning capabilities will yield unparalleled opportunity for organizations to drive business value and create a competitive advantage.
Ask a CIO where their focus lies and ‘digital transformation’ as well as ‘growth’ will come into the conversation quite quickly. The former sees growing investment in data analytics to become data-driven (45% of organizations expect to increase their spending in this area) while the latter is fueled by disruptive technology and the adoption of AI (41% of organizations name it as their game changer).
Whether you realized it or not, Data Privacy Day 2019 ( yes, it exists! ) has already come and gone. But this year, it was perhaps more significant than most not only because topics of bias, interpretability, and transparency in AI have moved to the forefront, but because the Council of Europe amended their Convention for the Protection of Individuals with regard to Automatic Processing of Personal Data.
ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!
In the span of a week, the integrated risk management (IRM) technology market has experienced significant consolidation. Four vendors from Gartner’s inaugural 2018 IRM Magic Quadrant have joined forces to evolve their legacy governance, risk and compliance (GRC) offerings to better compete in the IRM market (see figure below). Last Monday, market challenger ACL announced the acquisition of market visionary Rsam.
When Cloudera was formed about 10 years ago, the founders believed that companies would jump at the chance to store, manage, and analyze their data in the cloud. Thus, they came up with the name Cloudera, which was a play on “era of cloud.” But, much to their surprise, companies weren’t ready for cloud; they were more focused with on-prem. So, Cloudera focused on helping companies with storing, managing, and analyzing data on-prem.
Originally, I was planning to write a Further Exploration post on just Treemap variations. I thought there would only be a small, handle-full of charts that I would need to cover. But man, I was wrong. Once I actually sat down and begun researching into other Treemap types out there, I found myself surprised and overwhelmed. This was largely thanks to the work done by Hans-Jörg Schulz in his treeviz.net project.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Can Citizen Data Scientists Support Advanced Analytical Needs? No business, large or small, has unlimited funds and resources. In a world where data analytics is more important than ever to the business bottom line and competitive position, the typical business cannot afford to hire dozens of data scientists but it absolutely must have access to detailed, clear data analysis that will drive the bottom line and ensure success.
The Magic Quadrant (MQ) is an established, widely-referenced series of research reports published by the analyst firm Gartner, Inc. The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. A total of 19 vendors satisfied Gartner’s extensive inclusion criteria for insertion in this year’s MQ DMSA report.
I got to the end of the free WordPress account for my small business account and I wanted to analyse my CRM and sales data better. I wanted to dial up my sales and marketing, and, of course, use data to understand my audience better. With the free WordPress edition, I could not do some of the things that I wanted, such as HubSpot integration and advanced analytics.
Change is sometimes difficult to embrace, especially when it involves downtime. Autodesk, makers of world-renowned 3D design, engineering, and entertainment software, wanted to change from perpetual licensing to subscription-based licensing, but knew that this change would likely impact the entire. The post Autodesk Transforms, by Leveraging Data Virtualization appeared first on Data Virtualization and Modern Data Management.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
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