Smart Data Collective

JUNE 15, 2022

One of the secrets to attracting and retaining customers is to become more data-centric. trillion in 2019? According to many surveys, more than 90% of retail organizations across a wide range of sectors feel location data is crucial to their success. The retail industry is expanding all the time.

Advertising 98

Advertising Cost-Benefit ROI Sales 98

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. It is a database query language for accessing data and querying, updating, and managing relational database systems.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world. Connected Retail.

Technology 279

Technology Internet of Things IT IoT 279

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). Flight delay data analysis.

Data Warehouse 52

Data Warehouse Cost-Benefit Statistics Data Processing 52

Smart Data Collective

OCTOBER 14, 2019

.” Doing this protects the privacy of the people involved by ensuring that a malicious person could not trace a data source back to a single individual or otherwise reveal their identity. In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool.

Data Science 68

Data Science Machine Learning Big Data Interactive 68

Domino Data Lab

AUGUST 8, 2019

Sci Foo 2019. Data science teams should watch what’s happening here, especially the emphasis in the EU. For example, meeting Carole Goble was one of the top highlights of Sci Foo 2019 for me. They tend to use less machine learning, but more advanced statistical practices, since the outcomes (government policies, etc.)

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

datapine

SEPTEMBER 16, 2022

But often that’s how we present statistics: we just show the notes, we don’t play the music.” – Hans Rosling, Swedish statistician. They can be fun and interactive, too. 11) “Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks” by Jonathan Schwabish. datapine is filling your bookshelf thick and fast.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Having more data is generally better; however, there are subtle nuances. Use of influence functions goes back to the 1970s in robust statistics.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

datapine

FEBRUARY 23, 2023

2) Charts And Graphs Categories 3) 20 Different Types Of Graphs And Charts 4) How To Choose The Right Chart Type Data and statistics are all around us. That is because graphical representations of data make it easier to convey important information to different audiences. Table of Contents 1) What Are Graphs And Charts?

Visualization 177

Visualization Dashboards Sales Measurement 177

Sisense

DECEMBER 11, 2019

Periscope Data provides the ideal platform for data teams to establish an effective analytics environment in the type of emerging companies that are so prevalent in Israel. It’s why Sisense, having merged with Periscope Data in May 2019, chose to host this event in Tel Aviv. What VCs want from startups.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

O'Reilly on Data

MAY 21, 2019

Thus, many developers will need to curate data, train models, and analyze the results of models. With that said, we are still in a highly empirical era for ML: we need big data, big models, and big compute. A typical data pipeline for machine learning. Source: O'Reilly. Source: O'Reilly.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company. The accuracy of the predictions depends on the data used to create the model. Mobile Analytics.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

O'Reilly on Data

JANUARY 25, 2021

The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. Enough preliminaries.

Machine Learning 363

Machine Learning Software Testing Technology 363

Andrew White

JANUARY 11, 2021

But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. New data suggests that pinpoint or targeted efforts are likely to be more effective. We do have good examples and bad examples.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Yes—but basic dashboards won’t be enough.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52