Occam's Razor
OCTOBER 24, 2016
Culture is a stronger determinant of success with data than anything else. Including data. [People + Process + Structure] > [Data + Technology]. It seems hard to believe. Yet, it is so fantastically true. At least for now. At least until AGI takes over. Why is this formula material? The first part of the equation, for better or for worse, improves in an evolutionary manner.
The Unofficial Google Data Science Blog
OCTOBER 31, 2016
By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior. Some people seemed to be naturally good at doing this kind of high quality data analysis.
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Information Builders
MAY 12, 2016
Today is National Book Lover’s Day, and the perfect opportunity to indulge your inner bookworm. According to a Huffington Post blog on the occasion, one of the best ways to celebrate is by giving the gift of reading and passing along a favorite book to others who might enjoy it. With that in mind, we asked some Information Builders colleagues for their best “data reads” and below is a sampling of their suggestions: read more.
Darkhorse
AUGUST 19, 2016
We've explored improving our bar charts , data tables , and pie charts – all with the maxim: remove to improve. In this new installment of our Data Looks Better Naked series, we take on maps. More specifically, the choropleth map. There are libraries with entire floors devoted to the art and science of cartography so, clearly, this animation is general advice for one specific type of map.
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ScienceSoft
FEBRUARY 22, 2016
Now that Meaningful Use transforms into the value-based care delivery model, providers face a major challenge of adapting to the changes in how care delivery is organized, measured and reimbursed. No gilding any pills here, it is the ‘Do or Die’ dilemma. Find out how the healthcare data analytics can solve this dilemma.
Data Science and Beyond
SEPTEMBER 19, 2016
Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. I recently gave a talk where I argued the importance of asking Why , touching on three different topics: stakeholder motives, cause-and-effect relationships, and finding a sense of purpose.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
DataRobot Blog
JANUARY 16, 2016
Having a hero / heroine helps you navigate through the difficult times. You look up to them and then think that the problems you thought were difficult are actually trivial in nature. If people can solve and deliver at a much larger scale, you can too! Read more. The post 24 Ultimate Data Scientists To Follow in the World Today appeared first on DataRobot AI Cloud.
Rita Sallam
NOVEMBER 11, 2016
Everyone experiences rites of passage into adulthood. Sometimes it’s marriage, having a child, or just graduating from college where we mentally morph from idealistic, passionate, and carefree teenagers into responsible adults. As a long-time observer and some would say that stern 1 st grade teacher of Tableau since its early childhood, it is clear to me that Tableau has now put on its big girl pants – and Tableau 2016, its annual user conference, with more than 13,000 attendees was Table
In(tegrate) the Clouds
JUNE 23, 2016
This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses. Integration has to support the continuum of data velocities starting from batch all the way to continuous streams.
Ms SQL Girl
MAY 19, 2016
As you may already know In-database Analytics (also known as Advanced Analytics) is available in SQL Server 2016. To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. Read the official definition here. Check Out SQL Latest Bits. SQL Server 2016 RC3 : this includes SQL Server R Services that you can install.
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
Occam's Razor
DECEMBER 12, 2016
There is, almost literally, an unlimited number of things you could focus on to create a high impact data-influenced organization. And, as if unlimited is not enough, nearly every month your analytics vendors release new features, you discover new analytics solutions, and as your business is more successful (hurray!) there is a new mobile app to track or a new digital experience to problem-solve or a crazy online to offline campaign that upends everything unleashes a new layer of tactical activi
The Unofficial Google Data Science Blog
AUGUST 31, 2016
By DAVID ADAMS Since inception, this blog has defined “data science” as inference derived from data too big to fit on a single computer. Thus the ability to manipulate big data is essential to our notion of data science. While MapReduce remains a fundamental tool, many interesting analyses require more than it can offer. For instance, the well-known Mantel-Haenszel estimator cannot be implemented in a single MapReduce.
Information Builders
APRIL 4, 2016
Today is National Book Lover’s Day, and the perfect opportunity to indulge your inner bookworm. According to a Huffington Post blog on the occasion, one of the best ways to celebrate is by giving the gift of reading and passing along a favorite book to others who might enjoy it. With that in mind, we asked some Information Builders colleagues for their best “data reads” and below is a sampling of their suggestions: read more.
Bruno Aziza
DECEMBER 21, 2016
The Internet of Things provides fertile ground for marketing, but it is a minefield for the Ethical Use of Data.
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ScienceSoft
APRIL 7, 2016
Back from a visit to Retail Technology Show USA 2016, we compiled this year’s retail software development trends in one bite-size guide.
Data Science and Beyond
AUGUST 4, 2016
Data science can be defined as either the intersection or union of software engineering and statistics. In recent years, the field seems to be gravitating towards the broader unifying definition, where everyone who touches data in some way can call themselves a data scientist. Hence, while many people whose job title is Data Scientist do very useful work, the title itself has become fairly useless as an indication of what the title holder actually does.
Jim Harris
JANUARY 1, 2016
Once upon a time when asked on Twitter to identify a list of critical topics for data quality practitioners, my pithy (with only 140 characters in a tweet, pithy is as good as it gets) response was, and especially since I prefer emphasizing the need to take action, to propose six critical verbs: Investigate , Communicate , Collaborate , Remediate , Inebriate , and Reiterate.
MLWhiz
DECEMBER 23, 2016
This is a post which deviates from my pattern fo blogs that I have wrote till now but I found that Finance also uses up a lot of Statistics. So it won’t be a far cry to put this on my blog here. I recently started investing in Mutual funds so thought of rersearching the area before going all in. Here is the result of some of my research.
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Martha Bennett
NOVEMBER 2, 2016
Few would disagree that for IoT to live up to its promises, devices will sooner or later need to communicate directly, autonomously and securely with each other. Well-architected blockchain-based systems can help deliver those requirements, but they’re not available or even feasible today. In many ways, that’s a good thing, because it opens up great […].
In(tegrate) the Clouds
AUGUST 4, 2016
In my last post, I wrote about the new data integration requirements. In this post I wanted to share a few points made recently in a TDWI institute interview with SnapLogic founder and CEO Gaurav Dhillon when he was asked: What are some of the most interesting trends you’re seeing in the BI, analytics, and data warehousing space? There are three trends that I believe are fundamentally changing the world of data.
Jenny Sussin
OCTOBER 17, 2016
Over the last week, there have been a series of articles dumping on one particular social media monitoring application that was allegedly using an unethical value proposition to market its solution: surveillance. As one of Gartner’s social analytics analysts I’ve got to tell you, the tools that each vendor offers to the market could allow the exact same type of use.
Occam's Razor
AUGUST 9, 2016
Being book smart is good. The outcome of book smart is rarely better for analytics practitioners then folks trying to learn how to fly an airplane from how-to books. Hence, I have been obsessed with encouraging you to get actual data to learn from. This is all the way from Aug 2009: Web Analytics Career Advice: Play In The Real World! Or a subsequent post about how to build a successful career: Web Analytics Career Guide: From Zero To Hero In Five Steps.
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The Unofficial Google Data Science Blog
JUNE 30, 2016
By IVAN DIAZ & JOSEPH KELLY Determining the causal effects of an action—which we call treatment—on an outcome of interest is at the heart of many data analysis efforts. In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. In observational studies treatment is assigned by nature, therefore its mechanism is unknown and needs to be estimated.
Darkhorse
AUGUST 26, 2016
How many times has this happened to you: You get to the end of a gruelling analytics project. You’ve tortured the data until it confessed. You’ve made a silk purse out of a sow’s ear. You’ve found the fountain of youth. Against all odds, you solved it and know without a doubt that you have the right answer. You are thrilled. All that effort was worthwhile.
Bruno Aziza
DECEMBER 15, 2016
By the end of 2016, businesses are projected to spend over $73 billion on cybersecurity, yet they’re no more secure for it. Why? We’ve been looking at the problem through the wrong lens; IT too often makes incremental changes instead of planning a forward-looking approach that takes into account both [.
ScienceSoft
OCTOBER 21, 2016
No more abstract patient engagement talks. Healthcare data analytics shows the way into transforming the level of patients' involvement in their health into a measurable value.
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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?
Data Science and Beyond
AUGUST 21, 2016
You’re a hotshot manager. You love your dashboards and you keep your finger on the beating pulse of the business. You take pride in using data to drive your decisions rather than shooting from the hip like one of those old-school 1950s bosses. This is the 21st century, and data is king. You even hired a sexy statistician or data scientist, though you don’t really understand what they do.
Rita Sallam
AUGUST 17, 2016
It’s been an exciting two weeks in the world of BI! Just yesterday, Saleforce announced its intention to buy smart data discovery vendor, BeyondCore, a new Visionary entrant to this year’s BI and Analytics Magic Quadrant ! At the end of July, Workday announced its intention to acquire Platfora , one of the original Hadoop-based data discovery vendors and new to the Niche quadrant of the MQ.
MLWhiz
OCTOBER 26, 2016
It has been quite a few days I have been working with Pandas and apparently I feel I have gotten quite good at it. (Quite a Braggard I know) So thought about adding a post about Pandas usage here. I intend to make this post quite practical and since I find the pandas syntax quite self explanatory, I won’t be explaining much of the codes. Just the use cases and the code to achieve them.
Martha Bennett
SEPTEMBER 26, 2016
We’ve entered the age of the customer, where powerful customers are disrupting every industry. In response, companies will have to change how they develop, market, sell, and deliver products and services directly to their customers and through their partners. CIOs and their teams are crucial to these strategic responses and will have to track transformation […].
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