CIO Business Intelligence

JANUARY 24, 2024

Using unstructured data for actionable insights will be a crucial task for IT leaders looking to drive innovation and create additional business value.” One of the keys to benefiting from unstructured data is to define clear objectives, Miller says. What are the goals for leveraging unstructured data?”

Data Strategy 134

Data Strategy Strategy Unstructured Data Data Governance 134

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? For example, a 2.5

Cost-Benefit 73

Cost-Benefit Enterprise Internet of Things Technology 73

BizAcuity

MARCH 1, 2019

There is a coherent overlap between the Internet of Things and Artificial Intelligence. IoT is basically an exchange of data or information in a connected or interconnected environment. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Future of IoT is AI.

IoT 56

IoT Internet of Things Big Data Data-driven 56

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. That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

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

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. Source: Cloudera.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44