Smart Data Collective

APRIL 13, 2021

By 2012, there was a marginal increase, then the numbers rose steeply in 2014. The instances of data breaches in the United States are rather interesting. Based on figures from Statista , the volume of data breaches increased from 2005 to 2008, then dropped in 2009 and rose again in 2010 until it dropped again in 2011. Employee training.

Testing 122

Testing Behavioral Analytics Data-driven Big Data 122

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Occam's Razor

MAY 14, 2012

A lot of digital analytics focuses on direct response (conversions, leads, etc.). But there is an additional valuable, and sexy, focus of our marketing we don't give enough analytical love: Branding! Bonus One: Read: Brand Measurement: Analytics & Metrics for Branding Campaigns ].

Measurement 128

Measurement Analytics Advertising Marketing 128

datapine

MAY 14, 2019

It is also wise to clearly make a difference between data science and data analytics in a business context so that the exploration of the fields bring extra value for interested parties. Hands down one of the best books for data science. It’s also one of the best books on data science around.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

AWS Big Data

APRIL 3, 2024

They recognize the importance of accurate, complete, and timely data in enabling informed decision-making and fostering trust in their analytics and reporting processes. He enjoys helping large companies with the adoption of cloud technologies, and his area of expertise is mainly focused on Data Analytics and Data Management.

Data Quality 89

Data Quality Visualization Metadata Metrics 89

datapine

SEPTEMBER 27, 2022

We have already given you our top data visualization books , top business intelligence books , and best data analytics books. This piece, published in 2012, offers a step-to-step guide on everything related to SQL. Now it’s time to ponder over our hand-picked list of the 20 best SQL learning books available today.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Rita Sallam

SEPTEMBER 11, 2020

Rather than just using some solely fun data like football/ soccer statistics – go Mo Salah! While we limited the Bake-Off to four vendors, we are highlighting videos below from vendors that were supposed to participate in our Show Floor Showdowns at Gartner’s Data and Analytics Summits in Dallas and London last March.

Statistics 96

Statistics Machine Learning Sales Data Science 96

AWS Big Data

JUNE 28, 2023

In this post, we provide step-by-step guidance on how to get started with near-real time operational analytics using this feature. With Aurora zero-ETL integration with Amazon Redshift, you can bring together the transactional data of Aurora with the analytics capabilities of Amazon Redshift. source) and Amazon Redshift (destination).

Data Warehouse 85

Data Warehouse Analytics Metrics Dashboards 85

Occam's Razor

MARCH 12, 2012

Is there anything in the analytics space that is so full of promise and hype and sexiness and possible awesomeness than "big data?" Clickstream + qualitative data + rigorous statistical analysis of outcomes + deep mining of data from competitive intelligence sources + rapid experiments + more. Your analytical gut instinct.

Big Data 127

Big Data Data-driven Unstructured Data Marketing 127

IBM Big Data Hub

JANUARY 10, 2023

To make it easy for clients to understand how to utilize this capability within NPS, a demonstration was created that uses flight delay data for all commercial flights from United States airports that was collected by the United States Department of Transportation (Bureau of Transportation Statistics). Prerequisites for the demo.

Data Warehouse 52

Data Warehouse Cost-Benefit Statistics Data Processing 52

Data Science and Beyond

JULY 22, 2018

I got my first data science job in 2012, the year Harvard Business Review announced data scientist to be the sexiest job of the 21st century. Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. Things have changed considerably since 2012.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

AWS Big Data

MARCH 21, 2024

In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation of the zero-ETL series that started with Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift.

Data Warehouse 88

Data Warehouse Metrics Statistics Optimization 88

Smart Data Collective

OCTOBER 17, 2022

zettabytes in 2012. Big data analytics from 2022 show a dramatic surge in information consumption. Consider the statistics from Domo that the number of home-based workers has increased from roughly 15% 18 months ago to more than 50% now (it was close to 100% at times during the epidemic). This is an increase from 64.2

Big Data 103

Big Data Data-driven Recreation/Entertainment Data Governance 103

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Predictive analytics, yeah, not so much.” Those workflows would feedback into your business analytics. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

JULY 7, 2022

This new role, combined with the creation of data lakes and the increasing use of cloud services, created new employment opportunities in data analytics, data architecture, and data management. In 2012 Davenport and Patil declared the data scientist was “ The Sexiest Job of the 21st Century.” The data scientist.

Metadata 52

Metadata Data-driven Insurance Statistics 52

Domino Data Lab

AUGUST 8, 2019

Plus, we’re seeing how these issues surface in regulated environments, which have increasingly become target use cases for the popular open source projects used for data analytics infrastructure: Spark, Jupyter, Kafka, etc. Data governance, for the win! will imply lots of consequences and potential disputes unless the evidence is sound.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Occam's Razor

JANUARY 10, 2011

This post is a collection of six things I wish I knew before I started my career in decision support systems (of which web analytics is just the latest incarnation). The smallest part of my success, and yours, will come from having the prefect implementation of the Omniture Marketing Suite or Google Analytics. Stop switching tools!

Analytics 120

Analytics Measurement Data-driven Optimization 120

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

Sisense

DECEMBER 11, 2019

An exciting slate of presentations took them on a journey from why to how they should use data analytics to optimize their operations successfully and maximize their business opportunities. Ziv Ben Naim, Client Services Analytics & Strategy Lead, AppsFlyer Maayan Dukas Kfir, Data Analyst, AppsFlyer. The impact on customers.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Occam's Razor

SEPTEMBER 21, 2015

We send out our multi-tab spreadsheets, our best Google Analytics custom reports , our great dashboards full of data , and more to the tactical layer of data clients. We added to your analytical skills a demand for business savvy. Second, between 2012 and 2013. conversion rate (it might not be statistically significant!).

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Domino Data Lab

MARCH 3, 2019

Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). Companies are applying AI in functional areas in which they likely have existing analytic applications, building atop that base. AI Adoption in the Enterprise: How Companies Are Planning and Prioritizing AI Projects in Practice (Feb 2019).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

FEBRUARY 3, 2023

All the behavior is tracked with standard analytics and reported through a dashboard so you can watch for robotic glitches. Power Advisor tracks statistics about performance to locate bottlenecks and other issues. Rocketbot Orquestador will manage them, running them as needed while compiling statistics.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

O'Reilly on Data

MAY 21, 2019

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Modernize existing applications such as recommenders, search ranking, time series forecasting, etc.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Domino Data Lab

SEPTEMBER 25, 2019

To support data scientists extract insights and accelerate their work, Domino reached out to Addison-Wesley Professional (AWP) for appropriate permissions to excerpt “Time Series and Autocorrelation” chapter from the book R for Everyone: Advanced Analytics and Graphics, Second Edition. Chapter Introduction: Time Series and Autocorrelation.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

This post describes the analytical issues which arise in such a setting, and what the data scientist can do about them. 1]" Statistics, as a discipline, was largely developed in a small data world. 1]" Statistics, as a discipline, was largely developed in a small data world.

Experimentation 61

Experimentation Testing Statistics Metrics 61

datapine

MAY 17, 2021

Data discovery is a term used to describe the process for collecting data from various sources by detecting patterns and outliers with the help of guided advanced analytics and visual navigation of data, thus enabling consolidation of all business information. What Is Data Discovery? But how do you begin adopting this mentality?

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161