CTOvision

JUNE 17, 2014

It it he analyzes the Top 30 LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science. We update our analysis of Top 30 LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science (Dec 2013) and find several interesting trends. Big Data and Analytics: 74,350 (100%).

Big Data 103

Big Data Analytics Groups Data 103

CIO

SEPTEMBER 20, 2023

We internally analyzed the improvements we had to provide and, together with the CIOs in all the countries where Mapfre operates, we defined a very solid strategy that aligns with the business objectives, and we’re implementing that now. And in what state is the execution of this strategic plan?

Cloud 148

Cloud Insurance Strategic Planning Strategy 148

Datavail

JULY 7, 2022

Meanwhile, in an informal survey of attendees at a recent Datavail webinar, the majority (75 percent) of attendees said that their organization was pursuing a “hybrid” (partly on-premises and partly in the cloud) strategy for business intelligence and analytics. High data volumes.

Analytics 52

Analytics Artificial Inteligence Cloud Artificial Intelligence 52

Datavail

SEPTEMBER 8, 2022

Big data presents challenges in terms of volume, velocity, and variety—but that doesn’t mean you have to suffer from a bloated IT ecosystem to address these challenges. In fact, many businesses can realize significant advantages from streamlining their data integration pipelines, trimming away unnecessary tools and services.

Data 40

Data Nonprofit Quality Assurance Education 40

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. No wonder only 0.5 percent of this potentially high-valued asset is being used.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Who needs a data lake?

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Altexsoft

APRIL 13, 2023

You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59