Rita Sallam

AUGUST 28, 2022

The first one happened at our Data and Analytics Summit in London this past May. Last week, we ran the Analytics and BI Bake-off at the Data and Analytics Summit in Orlando with 5,500 of our closest D&A friends! These were our first in-person Data & Analytics Summits since 2019. What Data Did We Use?

Analytics 52

Analytics Data Analytics Cost-Benefit Measurement 52

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 332

Management Machine Learning Experimentation Metrics 332

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. ML model interpretability and data visualization. St Paul’s from Madison London.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

FineReport

FEBRUARY 28, 2020

Enterprise reporting is a process of extracting, processing, organizing, analyzing, and displaying data in the companies. It uses enterprise reporting tools to organize data into charts, tables, widgets, or other visualizations. In this way, users can gain insights from the data and make data-driven decisions. .

Reporting 96

Reporting Enterprise Visualization Business Intelligence 96

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. www.erwin.com/blog/defining-data-governance/.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Timo Elliott

JANUARY 22, 2019

2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

Sisense

JUNE 9, 2021

Like pretty much everything else in the world, football has become more data-driven than ever, so when the 24 teams set out to win the championship on 11 June , you can bet your bottom Euro that each team’s tactics, formation, and training will be shaped by a mountain of data. We can’t wait!

Analytics 98

Analytics Data-driven Internet of Things Measurement 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.

Technology 279

Technology Internet of Things IT IoT 279

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. The What: Data Governance Defined. Data governance has no standard definition.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Smart Data Collective

JULY 24, 2019

At Smart Data Collective, we often emphasize the biggest trends in the field of big data. We have talked extensively about the application of big data in everything from large-scale marketing to criminal justice reform. However, the benefits of big data can also be extended to simpler, everyday tasks, such as scheduling.

Data Science 76

Data Science Big Data Software Data-driven 76

Sisense

JULY 6, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Employing Enterprise Data Management (EDM).

Enterprise 98

Enterprise Management Data Architecture Strategy 98

Smart Data Collective

MAY 27, 2021

With online data acquisition on the rise, we are treading into mostly uncharted waters. Industry-wide regulations in web scraping and other forms of automated data collection are practically non-existent and we probably shouldn’t expect any in the near future. Non-)Public data.

Data Strategy 132

Data Strategy Strategy Data Collection Big Data 132

Alation

FEBRUARY 8, 2022

The “data textile” wars continue! In our first blog in this series , we define the terms data fabric and data mesh. The second blog took a deeper dive into data fabric, examining its key pillars and the role of the data catalog in each. Because those closest to the data are best equipped to manage it capably.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

datapine

DECEMBER 28, 2021

Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! To get this journey started let’s look at the misleading statistics definition.

Statistics 363

Statistics Advertising Visualization Data mining 363

Jet Global

MAY 1, 2023

By leveraging data analysis to solve high-value business problems, they will become more efficient. This is in contrast to traditional BI, which extracts insight from data outside of the app. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52