O'Reilly on Data
NOVEMBER 21, 2018
The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science. In this episode of the Data Show , I spoke with Vitaly Gordon , VP of data science and engineering at Salesforce. As the use of machine learning becomes more widespread, we need tools that will allow data scientists to scale so they can tackle many more problems and help many more people.
Rocket-Powered Data Science
DECEMBER 16, 2018
In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. An example of a cold start problem is k -Means Clustering, where the number of clusters k in the data set is not known in advance, and the locations of those clusters in feature space ( i.e., the cluster means) are not known either.
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BA Learnings
JANUARY 10, 2018
Swiss cheese has holes in various places on different slices of cheese when you cut it up. Let’s imagine these holes reflect weaknesses in the system where mistakes can pass through, afterall no system is perfect. One mistake passing through a hole in one slice of cheese might remain unnoticed and not lead to a business catastrophe, if it's corrected.
David Menninger's Analyst Perspectives
DECEMBER 3, 2018
IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation. This also includes a new conversational assistant to help generate narrative explanations of displays and interactive queries.
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Occam's Razor
JANUARY 8, 2018
Like me, I'm sure you are working on complex challenges when it comes to data. Multi-petabyte data warehouses. Multi-touch, cross-channel attribution analysis. Media mix modeling. Predictive analytics. Human-centric analysis. Oh, and let's not forget the application of machine learning to every facet of your work. It is genuinely fun to work on these opportunities.
CIO Business Intelligence
DECEMBER 4, 2018
With more and more data at our fingertips, it’s getting harder to focus on the information relevant to our problems and present it in an actionable way. That’s what business intelligence is all about.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
ScienceSoft
DECEMBER 13, 2018
Setting up data quality management seems to be a blurry task? We show what a well-organized process looks like and enumerate the required tools. These best practices will help you improve the quality of your data and, ultimately, your decisions.
Data Science and Beyond
DECEMBER 23, 2018
I’ve been interested in the area of causal inference in the past few years. In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. Now, I believe I’ve finally found a book with practical techniques that I can use on real problems: Causal Inference by Miguel Hernán and Jamie Robins.
Martha Bennett
NOVEMBER 7, 2018
“The visionaries will forge ahead; those hoping for immediate industry and process transformation will give up.” This was the opening sentence of my blog post accompanying Forrester’s DLT/blockchain predictions for 2018. I’m repeating it here, because it’ll continue to hold true for 2019 — with one proviso: There’s a real risk that we’ll experience the beginning […].
John Wheeler
DECEMBER 18, 2018
Last week, I had the distinct privilege to join my Gartner colleagues from our Risk Management Leadership Council in presenting the Q4 2018 Emerging Risk Report. We hosted more than 500 risk leaders across the globe in our exploration of the most critical risks. The Q4 2018 Emerging Risks Survey, designed by Gartner, captures and analyzes senior executives’ opinions on emerging risks and provides actionable insight on identifying and mitigating these risks.
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
O'Reilly on Data
NOVEMBER 13, 2018
Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Let’s begin by looking at the state of adoption.
Rocket-Powered Data Science
JULY 30, 2018
Machine Learning is (or should be) a core component of any marketing program now, especially in digital marketing campaigns. The following insightful quote by Dan Olley (EVP of Product Development and CTO at Elsevier) sums up the urgency and criticality of the situation: “If CIOs invested in machine learning three years ago, they would have wasted their money.
BA Learnings
JANUARY 3, 2018
When we have a strong belief about something or a bias towards a particular opinion, we consciously or unconsciously seek out evidence that validates what we already believe. When we come across contrary evidence, our default behaviour is to ignore it, diminish it or in some cases, conclude that it’s wrong prematurely without exploring its merits. This behaviour is due to a cognitive bias known as confirmation bias.
David Menninger's Analyst Perspectives
NOVEMBER 21, 2018
Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds". Pushing the envelope in data capabilities and access, Tableau introduced the "Ask Data" feature, allowing users to prose natural language queries and receive a response, along with new data preparation capabilities and other enhancements to help data analysts.
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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.
Occam's Razor
FEBRUARY 6, 2018
If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage. It all starts with sharp focus. Consider these three scenarios….
Boris Evelson
NOVEMBER 14, 2018
Over the last five years, most large enterprises have slowly but surely matured from being data-aware to data-driven. They all collect data from operational and transactional applications; process the data into data lakes, data hubs, data warehouses, and data marts; and build business intelligence (BI) and analytics applications to understand what the data is telling […].
Bruno Aziza
SEPTEMBER 17, 2018
Now more than ever, businesses are deploying machine learning to drive business results. Learn about the state of machine learning in business today.
IBM Big Data Hub
MARCH 16, 2018
March 16, 2018 is the 25th anniversary of the Db2 relational database product on Linux UNIX and Windows. Over the past 25 years, this team has built the Db2 brand for the distributed product, complementing IBM’s Db2 mainframe offering and creating a market force.
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ScienceSoft
APRIL 3, 2018
Our big data consultants have come up with an easy guide to real-time big data analytics. We explain the term and describe a typical architecture, as well as share our thoughts about whether real-time analytics can be a competitive advantage.
Juice Analytics
JULY 6, 2018
Putting data on a screen is easy. Making it meaningful is so much harder. Gathering a collection of visualizations and calling it a data story is easy (and inaccurate). Making data-driven narrative that influences people.hard. Here are 25 more lessons we've learned (the hard way) about what's easy and what's hard when it comes to telling data stories: Easy: Picking a good visualization to answer a data question Hard: Discovering the core message of your data story that will move your audience to
Birst BI
DECEMBER 18, 2018
According to Gartner, more than 3,000 CIOs ranked Business Intelligence (BI) and Analytics as the top differentiating technology for their organizations. If BI and Analytics is such a game-changer, then why is the average adoption rate in organizations only 32%? Despite the efforts of Cloud BI vendors making it easier for users to acquire, explore, and analyze data sources without IT dependency, lack of data literacy and analytic skills still hinder widespread adoption for data-driven decision m
O'Reilly on Data
OCTOBER 11, 2018
The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems. In this episode of the Data Show , I spoke with Jacob Ward , a Berggruen Fellow at Stanford University. Ward has an extensive background in journalism, mainly covering topics in science and technology, at National Geographic , Al Jazeera, Discovery Channel, BBC, Popular Science , and many other outlets.
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Rocket-Powered Data Science
JULY 30, 2018
Below are the individual links to these Data Science, Artificial Intelligence and Machine Learning books, all of which are top sellers on Amazon… “The Book of Why: The New Science of Cause and Effect” “Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems” “Deep Learning (Adaptive Computation and Machine Learning)” “Applied Artificial Intelligence: A Handbook For Business Leaders
BA Learnings
MAY 6, 2018
Once you embark on a new business analyst job or project, chances are that you will try to avoid past mistakes and look for ways in which you can deliver better results. A lot can be said for this motivation. The beginning of a project is usually an opportunity for a fresh start. Regardless of how advanced your business analysis skills are, or how fine-tuned your business analysis process is, there is always room to do better.
David Menninger's Analyst Perspectives
OCTOBER 5, 2018
In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event , the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data.
Occam's Razor
MARCH 19, 2018
I worry about data’s last-mile gap a lot. As a lover of data-influenced decision making, perhaps you worry as well. A lot of hard work has gone into collecting the requirements and implementation. An additional massive investment was made in the effort to perform ninja like analysis. The end result was a collection trends and insights. The last-mile gap is the distance between your trends and getting an influential company leader to take action.
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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?
Boris Evelson
MARCH 2, 2018
In most enterprises, data access is a fait accompli: 72% of global data and analytics decision makers say that they can access the data they need to obtain insights in a timely manner. However, even the most modern BI tools that make data more accessible still require significant subject matter expertise to find the right […].
Bruno Aziza
NOVEMBER 11, 2018
Allstate is proving that an 87-year-old insurance company can adapt and compete on data and analytics.
IBM Big Data Hub
NOVEMBER 15, 2018
If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all.
The Unofficial Google Data Science Blog
JULY 17, 2018
by BILL RICHOUX Critical decisions are being made continuously within large software systems. Often such decisions are the responsibility of a separate machine learning (ML) system. But there are instances when having a separate ML system is not ideal. In this blog post we describe one of these instances — Google search deciding when to check if web pages have changed.
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