Sisense

OCTOBER 6, 2020

When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 7, 2023

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Rocket-Powered Data Science

JULY 14, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 165

Analytics Internet of Things Prescriptive Analytics Data Science 165

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. And more recently, we have also seen innovation with IOT (Internet Of Things). It definitely depends on the type of data, no one method is always better than the other.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

IBM Big Data Hub

NOVEMBER 3, 2023

Unlike magnetic storage (such as HDDs and floppy drives) that store data using magnets, solid-state storage drives use NAND chips, a non-volatile storage technology that doesn’t require a power source to maintain its data. What is NVMe?

Cost-Benefit 76

Cost-Benefit Enterprise Internet of Things Technology 76

DataRobot Blog

APRIL 1, 2018

Today, data integration is moving closer to the edges – to the business people and to where the data actually exists – the Internet of Things (IoT) and the Cloud. 3) The emergence of a new enterprise information management platform.

Analytics 40

Analytics IoT Internet of Things B2B 40

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

OCTOBER 3, 2018

In the data center and in the cloud, there’s a proliferation of players, often building on technology we’ve created or contributed to, battling for share. The opportunity has only grown with the advent of practical Internet of Things applications.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

Sisense

JULY 23, 2021

Data from technologically advanced connected venues (with powerful Wi-Fi systems, Internet of Things sensors, and more), Chris believes, will lead to a major transformation in how the Games are delivered and will provide more opportunities for learning going forward.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105