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 second part of the equation most frequently improves in a revolutionary manner.

Metrics 146

Metrics Modeling Marketing Optimization 146

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!)

Analytics 141

Analytics B2B Consulting Optimization 141

Occam's Razor

SEPTEMBER 13, 2016

Econsultancy/Lynchpin provides this description in the report: "There were 960 respondents to our research request, which took the form of a global online survey fielded in May and June 2016. Today's post comes from a source of deep pain. Analysis Ninjas are valued less than I would prefer for them to be. The post is also sourced from a recent edition of my newsletter, The Marketing – Analytics Intersect.

Modeling 127

Modeling Reporting Experimentation Strategy 127

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. These engineers and analysts were often described as “careful” and “methodical”. But what do those adjectives actually mean?

Data Science 106

Data Science Metrics Measurement Statistics 106

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.

Analytics 109

Analytics Scorecard Metrics Strategy 109

DataFloq

SEPTEMBER 21, 2021

(Reuters) - Facebook Inc said on Tuesday it has invested more than $13 billion in safety and security measures since 2016, days after a newspaper reported the company had failed to fix "the platform's ill effects" researchers had identified.

Measurement 226

Measurement Reporting IT 226

Occam's Razor

MAY 5, 2016

You don't use an ad blocker, right? Of course not! You would never want to take away the opportunity a content creator has online to monetize their work via ads. I know that at least some of you think I'm being sarcastic. I am not, and this post is all about getting the data to show you that I am indeed not being sarcastic. I am insanely excited that we can track ad blocking behavior in Google Analytics, so easily.

Metrics 103

Metrics Reporting Analytics Advertising 103

Ms SQL Girl

MARCH 30, 2016

As a side note, I actually was struggling to find Power View button in Excel 2016 as it was missing from the ribbon. The steps to connect to a Tabular Model in Excel 2013 are the same as in Excel 2016: In Excel 2013/2016, navigate to the Data menu and choose From Other Sources > From Analysis Services from the ribbon as shown below. It’s been a long time since I wrote an article on Tabular Model. This week, one of my good readers, Andrew posted me a question.

Modeling 40

Modeling Visualization IT Business Intelligence 40

Ms SQL Girl

MARCH 30, 2016

As a side note, I actually was struggling to find Power View button in Excel 2016 as it was missing from the ribbon. The steps to connect to a Tabular Model in Excel 2013 are the same as in Excel 2016: In Excel 2013/2016, navigate to the Data menu and choose From Other Sources > From Analysis Services from the ribbon as shown below. It’s been a long time since I wrote an article on Tabular Model. This week, one of my good readers, Andrew posted me a question.

Modeling 40

Modeling Visualization IT Business Intelligence 40

Occam's Razor

APRIL 4, 2016

Here's something important I've observed in my experience in working with data, and changing organizations with ideas: Great Analysts are always skeptical. Deeply so. This was always true, of course. But, it has become mission critical over the last few years as the depth, breadth, quantity and every other dimension you could apply to data has simply exploded. There is too much data. There are too many tables/charts/"insights" being rammed down your throat.

Marketing 93

Marketing Metrics Strategy IT 93

DataFloq

AUGUST 20, 2020

WASHINGTON (Reuters) - In an unprecedented case, a former chief security officer for Uber Technologies was criminally charged on Thursday with trying to cover up a 2016 hacking that exposed personal information of about 57 million of the ride-hailing company's customers and drivers.

Technology 351

Technology 351

Occam's Razor

JULY 6, 2016

Analysts, honestly, make the world go round when it comes to any successful business – yes, data is that important. As you might expect from any role, they also make a handful of important mistakes. I've written about the biggest mistake web analysts make. Today's post is an adjacent mistake: The cardinal sin of spending too much time with data and in reports!

Experimentation 86

Experimentation Testing B2B Advertising 86

Occam's Razor

JANUARY 4, 2016

For the last decade (#omg!), I've consistently complained about a fundamental flaw in Web Analytics tools: They incentivize one night stands , rather than engagements matching customer-intent. This leads to owners of digital experiences (insanely) expecting all visitors to their websites to convert right away – anything less than that is a failure. Damn the intent the customer is expressing.

Metrics 88

Metrics Key Performance Indicator Analytics Reporting 88

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. SQL Server 2016 RC3 : this includes SQL Server R Services that you can install. SQL Server 2016 CTP 3 Sample : provides sample databases and guidance on how to best explore the new features. Use Adventure Works SQL Server 2016 CTP 3 to try out different Hero features in SQL Server 2016.

Predictive Modeling 45

Predictive Modeling Statistics Analytics Modeling 45

Occam's Razor

FEBRUARY 10, 2016

If you don't have goals, you are not doing digital analytics. You are doing i am wasting earth's precious oxygenalytics. Let's back up. Let me start with a story. We were brain storming about the next cluster of coolness for Analytics, the conversation quickly went to what Analysts need to look at on a daily, weekly and monthly basis.

Key Performance Indicator 80

Key Performance Indicator Slice and Dice Analytics B2B 80

Occam's Razor

MAY 31, 2016

An off-topic post this week, to celebrate this incredible outpost you've helped create on the web, Occam's Razor. This month my beloved blog is ten years old. It feels more like five. But, I've already celebrated the blog being five years old ! I have to admit life has been a tad bit busy lately, and it took a note from a reader to remind me of the birthday.

Consulting 77

Consulting Advertising Marketing IT 77

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. A video of the talk is available below.

Data Science 66

Data Science Experimentation Predictive Modeling Deep Learning 66

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.

Data Science 66

Data Science Sales Broadcasting Optimization 66

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. SQL Server 2016 RC3 : this includes SQL Server R Services that you can install. SQL Server 2016 CTP 3 Sample : provides sample databases and guidance on how to best explore the new features. Use Adventure Works SQL Server 2016 CTP 3 to try out different Hero features in SQL Server 2016.

Predictive Modeling 40

Predictive Modeling Statistics Analytics Modeling 40

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.

Data Science 56

Data Science Statistics Software 56

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

Editor's note: The Google Sheets add-on described in this blog post is no longer supported externally by Google. By STEVEN L. SCOTT Big data is new and exciting, but there are still lots of small data problems in the world. Many people who are just becoming aware that they need to work with data are finding that they lack the tools to do so. The statistics app for Google Sheets hopes to change that.

Statistics 53

Statistics Data Science Big Data Testing 53

Rita Sallam

NOVEMBER 11, 2016

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 Tableau’s coming of age party. Everyone experiences rites of passage into adulthood.

Visualization 49

Visualization Metrics Enterprise Data Processing 49

Darkhorse

NOVEMBER 8, 2016

There is a near infinite variety of visualization methods within our field. Santiago Ortiz’s article, 45 ways to communicate two quantiles , shows us a stunning expanse for just two numbers. FlowingData has given us 9 ways to visualize proportions and 11 ways for changes over time. Many charting taxonomies include distributions, but they only present a few options. Let’s remedy that with a post on the many.

Visualization 71

Visualization Experimentation Measurement Statistics 71

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.

Data Science 52

Data Science Dashboards Data-driven Management 52

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.

Reporting 73

Reporting IT Visualization 73

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

IT 75

IT 75

Data Science and Beyond

JUNE 19, 2016

Much has been written in recent years on the pitfalls of using traditional hypothesis testing with online A/B tests. A key issue is that you’re likely to end up with many false positives if you repeatedly check your results and stop as soon as you reach statistical significance.

Data Science 52

Data Science Testing Statistics IT 52

Data Science and Beyond

MAY 14, 2016

Background: I have previously written about the need for real insights that address the why behind events, not only the what and how. This was followed by a fairly popular post on causality, which was heavily influenced by Samantha Kleinberg's book Why: A Guide to Finding and Using Causes.

Data Science 52

Data Science 52

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. Integration is event-based rather than clock-driven.

Data Integration 49

Data Integration Data Lake Data Warehouse Big Data 49

Data Science and Beyond

MARCH 20, 2016

Given the impressive advancement of machine intelligence in recent years, many people have been speculating on what the future holds when it comes to the power and roles of robots in our society. Some have even called for regulation of machine intelligence before it’s too late.

Data Science 52

Data Science IT 52

Data Science and Beyond

FEBRUARY 14, 2016

Everywhere you go these days, you hear about deep learning’s impressive advancements. New deep learning libraries, tools, and products get announced on a regular basis, making the average data scientist feel like they’re missing out if they don’t hop on the deep learning bandwagon.

Data Science 52

Data Science Deep Learning IT 52

Data Science and Beyond

JANUARY 23, 2016

Many modern data scientists don’t get to experience data collection in the offline world. Recently, I spent a month sailing down the northern Great Barrier Reef, collecting data for the Reef Life Survey project.

Data Science 52

Data Science Data Collection Machine Learning 52

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

IT 70

IT 70

TIBCO

FEBRUARY 22, 2016

Silos, not the tall towers used for grain storage, but the pesky divisions and hierarchies that are rampant across many organizations and largely resistant to destruction. They take many forms, and once established, prove to be tenacious and embedded; keeping people in their boxes, marginalized and isolated, cementing a ‘them and us’ culture, which remains the perennial gripe of corporate life.

Snapshot 40

Snapshot Statistics Data Analytics Visualization 40

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

Measurement 70

Measurement Modeling Data Analytics Analytics 70

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. The first is the shift to the cloud.

Internet of Things 45

Internet of Things Data Lake Data Warehouse Predictive Analytics 45

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.

Data Science 44

Data Science Statistics Experimentation Optimization 44

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

Measurement 61

Measurement Data Analytics IT Analytics 61

Martha Bennett

FEBRUARY 17, 2016

At the 2016 SAP Insider event on BI/Hana in Las Vegas, SAP announced the acquisition of independent mobile BI specialist Roambi’s solution portfolio and key assets. Major conferences are often the occasion for key vendor announcements, and SAP didn’t disappoint. With this acquisition, SAP underlines its commitment not only to mobile and cloud but also […]. application development & delivery business intelligence cloud computing

IT 40

IT Business Intelligence 40

In(tegrate) the Clouds

MARCH 7, 2016

Last week SnapLogic posted the company’s mission on their blog , which is focused on accelerating how enterprise integration technology is delivered in the enterprise. The company is growing rapidly and hiring. Here is the their mission statement: It’s time to rethink integration. Integrating data and applications with legacy products is slowing down your business. What you’re running now is no longer running fast enough for today’s business needs.

Enterprise 45

Enterprise IT Strategy Marketing 45

Jim Harris

SEPTEMBER 1, 2016

Plato’s Cave is a famous allegory from philosophy that describes a fictional scenario where people mistake an illusion for reality. The allegory describes a group of people who have lived their whole lives as prisoners chained motionless in a dark cave, forced to face a blank wall. Behind the prisoners is a large fire. In front of the fire are puppeteers that project shadows onto the cave wall, acting out little plays, which include mimicking voices and sound effects that echo off the cave walls.

Interactive 61

Interactive IT Data Quality 61

Jenny Sussin

JULY 12, 2016

I’ve seen some funny memes online where a big scary van has graffiti’ed “Rare Pokemon Inside” on it with the caption, “How to kidnap a 28 year old in 2016,” and I can tell you, that is accurate. I’m smack dab in the middle of Pokemon Go ‘s target demographic.

Technology 40

Technology IT 40

The Unofficial Google Data Science Blog

JULY 31, 2016

By JEAN STEINER Randomized A/B experiments are the gold standard for estimating causal effects. The analysis can be straightforward, especially when it's safe to assume that individual observations of an outcome measure are independent. However, this is not always the case. When observations are not independent, an analysis that assumes independence can lead us to believe that effects are significant when they actually aren't.

Data Science 42

Data Science Experimentation Testing Measurement 42