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A Tale of Two Acquisitions… It’s back to the BI future! This week, Cloud megavendors Google and Salesforce bought modern analytics and BI vendors Looker and Tableau, respectively, to complement their cloud data management and application stacks and to drive data and compute-intensive analytics use cases to their respective clouds. The modern analytics and BI market is now mainstream with large enterprises now deploying these platforms enterprise wide.
Companies across the continent are rapidly adopting cloud services to improve efficiency, scalability and access. However, this rapid adoption of cloud services is seeing an exponential rise in attacks and vulnerabilities. One of the core functions of CISO Cape Town is for IT security experts to gather and share new strategies to defend against the online realm, strategies that may incorporate traditional applications, and in other cases tackle challenges differently.
Overview Bayes’ Theorem is one of the most powerful concepts in statistics – a must-know for data science professionals Get acquainted with Bayes’ Theorem, The post An Introduction to the Powerful Bayes’ Theorem for Data Science Professionals appeared first on Analytics Vidhya.
This year, I attended Informatica World 2019, Informatica's annual user conference. The main focus this year was on the cloud with a heavy does of AI. Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.
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.
Using daily and/or weekly sales reports with your team may be the single most powerful action you can take to increase your team’s performance. Don’t believe us? We’ll convince you with an example from another sector – fitness. Let’s say a friend of yours has a goal of losing 10 pounds of fat or gaining 5 pounds of muscle, over the next 2 months. Your friend excitedly tells you their plan, and all of the actions they plan to take to achieve their goal.
Welcome to Future Enterprise Systems Africa (FESA 2019) , our new conference born out of the DigiCon series of events. The slight shift in focus is to hone in on the practical steps of digital transformation the nuts and bolts of what the next generation business requires in order to survive. Two key areas were identified – the architecture teams and the innovation teams.
Overview TensorFlow.js (deeplearn.js) enables us to build machine learning and deep learning models right in our browser without needing any complex installation steps There. The post Build a Machine Learning Model in your Browser using TensorFlow.js and Python appeared first on Analytics Vidhya.
Overview TensorFlow.js (deeplearn.js) enables us to build machine learning and deep learning models right in our browser without needing any complex installation steps There. The post Build a Machine Learning Model in your Browser using TensorFlow.js and Python appeared first on Analytics Vidhya.
Qonnections 2019 is Qlik's annual user conference. Key news from this year's conference centered on acquisitions of Podium Data and Attunity, along with an expansion of certifications on Google Cloud Platform, AWS, and Azure, with the ability to support Red Hat OpenShift. Many of these announcements were centered on a key theme of a cloud and SaaS-first approach.
Salesforce.com’s $15.7 billion bid for Tableau Software has many organizations wondering how the proposed acquisition will impact their operations. According to industry analysts, it all depends on how your enterprise makes use of their respective platforms. Users of Salesforce’s CRM platform have all subscribed to its software-as-a-service (SaaS) model, putting their data in the cloud — but the company is only beginning to respond to the demand for sophisticated tools to analyze that data. [ De
Introduction “I don’t want a full report, just give me a summary of the results” I have often found myself in this situation – The post Comprehensive Guide to Text Summarization using Deep Learning in Python appeared first on Analytics Vidhya.
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
I recently did an Innovation Evangelist podcast with Tom Raftery , covering the top innovation trends that I find interesting in business and society today. Here’s a summary of some of the points we covered in the video above: 1. We have a golden opportunity to make the world a better place. Technology is accelerating, and it’s amazing opportunity for win-win-win opportunities.
Sustainability is a major concern for many businesses. You probably wouldn’t think that data analytics would be the core solution. Many people believe that the fields of big data and green business have little overlap. However, big data could actually be a wonderful solution for many sustainability problems. People that know me are aware that I have a blog on sustainability, as well as Smart Data Collective.
Digital transformation examples can be found almost anywhere, in almost any industry. Its past successes – and future potential – are well documented, chronicled in the billion-dollar valuations of the frontrunners in the practice. Amazon began as a disruptor to brick-and-mortar bookstores, eventually becoming one of the most obvious digital transformation examples as it went on to revolutionize online shopping.
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.
Getting your first data science job might be challenging, but it’s possible to achieve this goal with the right resources. Before jumping into a data science career , there are a few questions you should be able to answer: How do you break into the profession? What skills do you need to become a data scientist? Where are the best data science jobs? First, it’s important to understand what data science is.
Big data is everywhere , and it’s finding its way into a multitude of industries and applications. One of the most fascinating big data industries is manufacturing. In an environment of fast-paced production and competitive markets, big data helps companies rise to the top and stay efficient and relevant. Manufacturing innovation has long been an integral piece of our economic success, and it seems that big data allows for great industry gains.
(Jeremy Vale and Paolo Santamaria contributed to this post.) This month’s Insights Beat focuses on the latest research in our insights-driven playbook; showcases multiple data, analytics, and machine-learning vendor evaluations; and shines a light on B2B analytics techniques. Is Your Data Strategy Lacking? Time To Sound The Alarm In order to compete in the age of […].
New product releases are exciting, but can also come with some amount of confusion; how will the tool you know and love change? Will your workflow need tweaking? And most importantly, how will you learn to use new features fluently? We looked at the four best ways to focus your exploration and take advantage of new feature releases.
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.
Data stories use the techniques of traditional storytelling — narrative flow, context, structure — to guide audiences through data and offer flexibility to find insights relevant to them. Data may be the star, but your data story won’t cohere without a mix of additional ingredients. There are at least four things that you’ll want to incorporate into your data story that go beyond the data visualizations: 1.
Google is taking privacy more seriously these days. Last year, the Washington Post reported that they adopted some new big data security standards. Some of these standards were put into place to improve Gmail security. However, there are still a lot of measures that Gmail users themselves need to take. Big data is making it easier to keep your Gmail secure , but only if you take the right precautions.
I was recently interviewed on the future of analytics by Tamara McCleary, CEO of Thulium, a social media analytics and consulting agency, for her new “Tech Unknown” podcast. You can read her blog post summary or listen to the podcast directly below. We explored the current state of the art for AI/ML-driven analytics and talked about what business leaders can do prepare for what’s to come: Ways AI and ML-driven analytics drive better business outcomes.
This post provided a distilled overview regarding the rediscovery of 50,000 samples within the MNIST dataset. . MNIST: The Potential Danger of Overfitting. Recently, Chhavi Yadav (NYU) and Leon Bottou (Facebook AI Research and NYU) indicated in their paper, “ Cold Case: The Lost MNIST Digits ”, how they reconstructed the MNIST (Modified National Institute of Standards and Technology) dataset and added 50,000 samples to the test set for a total of 60,000 samples.
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!
An Interview with Jamie Cousin, FP&A Manager at ServiceMaster. What exactly leads to customer loyalty – and what can the business do to increase it? The FP&A team at ServiceMaster is searching for answers deep in the individual experiences and purchase histories of over 2 million customers with assistance from the new Artificial Intelligence capabilities embedded in Jedox software.
Big data is changing the future of gaming. Dataiku’s Pierre Gutierrez presented a compelling analysis of the role of data analytics in gaming in his piece A Flood Of Gaming Analytics Data With No End In Sight. Some of the ways that data analytics has changed the gaming industry are not noticeable to the average gamer. They don’t directly see the impact, but data is changing the gaming experience in many ways.
Salesforce acquires Tableau – June 2019 (business app vendor acquires analytics/BI). Google acquires Looker – June 2019 (infrastructure/search/data broker vendor acquires analytics/BI). Salesforce closes acquisition of Mulesoft – May 2018 (business app vendor acquires data integration). Then again, classifying vendors as I do above is a loss leader – the classifications do not make sense any more since most large vendors play in many spaces.
Read why IBM has just launched the inaugural IBM Women Leaders of AI , and why we’re honoring women pioneering AI in their businesses in diverse industries from across the globe.
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.
At Sisense, our mission is to empower users of all kinds with deep insights from even the most complex data. This requires a focus on many different areas of analytics including our ability to work with large, complex, disparate data; our ability to provide an easy to use interface for both working with data and building analytics; and our ability to go beyond dashboards with capabilities such as IoT integration and powerful APIs to support application developers.
Big data is changing our lives in many ways. Some of the ways data impacts us are much more subtle than others. One example is with digital calendars. A number of new data algorithms are being used to make digital calendars more effective. Big data is so important for event planning and preparation. A growing number of companies are using big data to plan their events more effectively.
If you haven’t already upgraded to the latest version of Jet, here is a great reason to do so! Version 20.0 ( released April 30th 2019 ) includes a new Word integration feature that makes including your data, charts, and graphs from Jet Reports into a Word document a snap! Join us for a full tour of the new Word Integration feature while we walk you through real-world examples for why and how to use it!
I want to comment in an insightful and challenging Opinion piece in this last weekends US print edition of the Wall Street Journal. The article was titled, A Dearth of Data Helped Hong Kong Succeed , and it was written by Jairaj Devadiga. The article explains an odd fact that Hong Kong’s economic policy management during a period of high growth was correlated with a lack of central (e.g. federal) government planning and that was driven by a lack of data about the economy.
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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