Occam's Razor

JUNE 28, 2007

I find that there is a bunch of confusion about sampling your data and implications of making that decision (other than that if you sample the data you'll save money). So here's the 411 on data sampling. There are three primary ways of sampling your data. Code Orange : Sampling data collected from each page.

Analytics 74

Analytics Statistics Data Collection Cost-Benefit 74

Occam's Razor

FEBRUARY 22, 2010

These toolbars also collect limited information about the browsing behavior of the customers who use them, including the pages visited, the search terms used, perhaps even time spent on each page, and so forth. Typically, data collected is anonymous and not personally identifiable information (PII). 6: Self-reported Data.

Metrics 124

Metrics Advertising Reporting Data Collection 124

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. For example, you could tell your phone about the trip you plan and it would book the most convenient flight, hotel and rental car for you.

Technology 279

Technology Internet of Things IT IoT 279

Smart Data Collective

JUNE 15, 2022

Accurate client data collection and analysis are critical to maximizing all of these activities. When customers visit your website, they generate data points that may be mined for important insights about what works and what doesn’t on your site. Better Understand Customer Demographics.

Advertising 111

Advertising Cost-Benefit Sales ROI 111

Occam's Razor

MARCH 30, 2017

The solution was to leverage real-time signals like bad weather, flight delays at 5,145 airports, and other such data, combine that with ML powered algorithms to automate ads and messaging in the proximity of local airports. 60% increase in bookings in targeted areas. We are needed today because data collection is hard.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Sisense

APRIL 10, 2020

NLP can be used on written text or speech data. For our example, we will use written text for our comparison of R vs Python for data science. We are surrounded by written text every day: emails, SMS messages, webpages, books, and much more. R vs Python for data science: Digging into the differences.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Occam's Razor

JUNE 6, 2007

I am thrilled to say that my book Web Analytics: An Hour A Day has been published and is now widely available. It has been such an amazing journey to write the book, and for it to come up almost exactly a year after I started this blog. Damini, Chirag and now the book! :). Part One: The book (my side of the story, details).

Analytics 60

Analytics Metrics Marketing Dashboards 60

datapine

FEBRUARY 9, 2024

4) How to Select Your KPIs 5) Avoid These KPI Mistakes 6) How To Choose A KPI Management Solution 7) KPI Management Examples Fact: 100% of statistics strategically placed at the top of blog posts are a direct result of people studying the dynamics of Key Performance Indicators, or KPIs. 3) What Are KPI Best Practices? Bernard Marr.

KPI 221

KPI Management Key Performance Indicator Measurement 221

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. We discussed this as far back as Chapter 1 [in the book]. There is also a complementary Domino project available.

Testing 68

Testing Modeling Interactive Measurement 68

Jet Global

MAY 15, 2020

Book Value Per Share. Price-to-Book Value Ratio. Book Value Per Share (BVPS) – This is by far insightsoftware’s preferred valuation KPI. Price-to-Book Value Ratio – This financial performance indicator measures a company’s share price relative to its book value. Earnings Per Share. Levered Cash Flow.

Metrics 98

Metrics Finance Reporting KPI 98

Data Science 101

OCTOBER 31, 2019

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Data Collection. Regression.

Data mining 77

Data mining KDD Data Science Knowledge Discovery 77

FineReport

MAY 18, 2024

Scatter Plots Scatter plots depict the relationship between two numerical variables by plotting individual data points on a graph. This technique helps identify correlations or patterns between variables and is widely used in statistical analysis and research studies.

Visualization 52

Visualization Interactive Cost-Benefit Dashboards 52

FineReport

JUNE 29, 2023

Advanced levels of IoT analytics dashboards facilitate the identification of statistical trends, enabling the use of data for predictive failure analysis and extracting precise information and correlations from datasets. Generally, the primary objective of any IoT device in a connected environment is data collection.

IoT 52

IoT Dashboards Visualization Cost-Benefit 52

Domino Data Lab

OCTOBER 23, 2019

As Domino is committed to supporting data scientists and accelerating research, we reached out to Addison-Wesley Professional (AWP) Pearson for the appropriate permissions to excerpt “Predicting Social-Media Influence in the NBA” from the book, Pragmatic AI: An Introduction to Cloud-Based Machine Learning by Noah Gift.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. You saw in the previous chapter that conditioning can break statistical dependence. Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Depict Data Studio

APRIL 16, 2019

Long ago, I had majored in psychology so I could take as many research methods and statistics courses as possible. And learning how we learn–the courses on cognition, memory, perception, and brain biology–are critical in my everyday work as a data visualization designer and speaker. What an easy Five Minute Fix!

Visualization 56

Visualization Reporting Statistics Dashboards 56

Depict Data Studio

AUGUST 18, 2020

I used to write hundred-page reports… I was trained to write lengthy reports filled with statistical jargon. My audience can understand the information, so the data actually gets used. Can’t I just find this information on the internet or in books?! Important information sat around and gathered dust. More graphs.

Reporting 52

Reporting Visualization Dashboards Consulting 52

The Unofficial Google Data Science Blog

APRIL 17, 2017

Our rationale was in accord with the views expressed in the online forecasting book by Hyndman and Athana­sopou­los [1], who after mentioning the potential utility of an "explanatory model" write: However, there are several reasons a forecaster might select a time series model rather than an explanatory model. Forecasting data and methods".

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

FineReport

JUNE 26, 2023

These reports commonly incorporate graphical elements such as charts, graphs, tables, and statistics, which complement the text-based information and offer visual representation. Gather Relevant Data : Collect accurate and relevant data from reliable sources.

Reporting 52

Reporting Key Performance Indicator Sales Visualization 52

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Andrew White

JANUARY 9, 2022

We found anecdotal data that suggested things such as a) CDO’s with a business, more than a technical, background tend to be more effective or successful, and b) CDOs most often came from a business background, and c) those that were successful had a good chance at becoming CEO or CEO or some other CXO (but not really CIO).

Analytics 64

Analytics Measurement Data-driven Modeling 64

O'Reilly on Data

JULY 28, 2020

There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process. Conclusion.

Marketing 364

Marketing Experimentation Metrics Testing 364

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Use of influence functions goes back to the 1970s in robust statistics. That seems much more robust.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Depict Data Studio

MAY 8, 2023

Davey Strategies “I am a university researcher and have a lot of familiarity with data collection and statistical analysis programs/platforms (e.g. but needed a low-cost, widely-used data collection and analysis tool I could recommend and teach to the community partners with whom I conduct research.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. Experiment, or die.

Analytics 119

Analytics Consulting Metrics Experimentation 119

BizAcuity

JULY 7, 2020

With respect to developments or changes in inbound markets, gaming data, player statistics, economic recovery speed, and more, adjust and reiterate core strategies. Earlier, marketing campaigns were highly dependent on data. So, begin with resuming familiar and sure-to-work revenue management strategies.

Revenue Optimization 98

Revenue Optimization Measurement Interactive Marketing 98

datapine

AUGUST 29, 2022

With that in mind, we have prepared a list of the top 19 definitive data analytics and big data books, along with magazines and authentic readers’ reviews upvoted by the Goodreads community. Essential Big Data And Data Analytics Insights. Discover The Best Data Analytics And Big Data Books Of All Time.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

erwin

APRIL 21, 2020

The easiest way to understand a data catalog is to look at how libraries catalog books and manuals in a hierarchical structure, making it easy for anyone to find exactly what they need. So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance. What’s the best way to organize data and ensure it is supported by business policies and well-defined, governed systems, data elements and performance measures? What Is a Data Catalog?

Measurement 96

Measurement Sales Data Governance Metadata 96

Insight

MARCH 12, 2020

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often With breaking this bottleneck in mind, I’ve used my time as an Insight Data Science Fellow to build the AIgent, a web-based neural net to connect writers to representation. often without even looking at it.

Modeling 59

Modeling Metadata Publishing Sales 59

Jet Global

NOVEMBER 2, 2021

Those without KPIs are left without any valuable statistics, while those with established performance tracking dashboards are able to make data driven decisions. Setting up an insightful university KPI system requires three main components: effective data collection, an automated process, and realistic goals.

Metrics 52

Metrics Reporting KPI Key Performance Indicator 52

Jet Global

MAY 1, 2023

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.”

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Data ingestion methods can include batch ingestion (collecting data at scheduled intervals) or real-time streaming data ingestion (collecting data continuously as it is generated). Technologies used for data ingestion include data connectors, ingestion frameworks, or data collection agents.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

O'Reilly on Data

JUNE 16, 2020

We know, statistically, that doubling down on an 11 is a good (and common) strategy in blackjack. One way to correct for this bias in the data is to look at the statistics of “excess deaths,” the numbers when compared with previous years. Mike: But I lost! How can you say always ?!? The decision-making process was fine.

Uncertainty 358

Uncertainty Testing Risk Reporting 358