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 Data-driven 150

CIO Business Intelligence

JANUARY 24, 2024

With nearly 800 locations, RaceTrac handles a substantial volume of data, encompassing 260 million transactions annually, alongside data feeds from store cameras and internet of things (IoT) devices embedded in fuel pumps.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

CIO Business Intelligence

DECEMBER 13, 2023

Applications such as financial forecasting and customer relationship management brought tremendous benefits to early adopters, even though capabilities were constrained by the structured nature of the data they processed. have encouraged the creation of unstructured data.

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

CIO Business Intelligence

JUNE 28, 2022

Text by itself doesn’t have much structure to begin with, but when you’ve got a pile of text written by hundreds or thousands of employees over dozens of years, then whatever structure there is might be even weaker. Even structured data is often unstructured.

Management 138

Management Internet of Things Statistics Data Science 138

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 82

Analytics Data Warehouse Data Lake Metadata 82

datapine

AUGUST 20, 2019

Operations data: Data generated from a set of operations such as orders, online transactions, competitor analytics, sales data, point of sales data, pricing data, etc. The gigantic evolution of structured, unstructured, and semi-structured data is referred to as Big data.

Big Data 100

Big Data B2B Cost-Benefit Structured Data 100

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

AWS Big Data

MARCH 13, 2024

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS. You’re now ready to query the tables using Athena.

Analytics 112

Analytics IoT Metadata Internet of Things 112

Smart Data Collective

SEPTEMBER 26, 2019

Unstructured data lacks a specific format or structure. As a result, processing and analyzing unstructured data is super-difficult and time-consuming. Semi-structured. Semi-structured data contains a mixture of both structured and unstructured data.

Big Data 101

Big Data Software Unstructured Data Data Integration 101

CIO Business Intelligence

APRIL 4, 2024

“Make sure the data you have is discoverable by AI systems, which might mean building an enriched catalog using generative AI or using it to build an ontology on top of structured data,” he says. “In In many instances, it’s a significant improvement in productivity when using AI to streamline these workloads.

Enterprise 134

Enterprise Cost-Benefit Forecasting Sales 134

Cloudera

APRIL 2, 2019

Data-driven organizations – particularly those utilizing IoT – require low-latency, high-performance compute to process data at the edge in order to make faster, smarter decisions. It supports a wide variety of use cases from powering web & mobile applications to operationalizing IoT data.

Cost-Benefit 48

Cost-Benefit IoT Testing Machine Learning 48

Cloudera

OCTOBER 3, 2018

The tremendous growth in both unstructured and structured data overwhelms traditional data warehouses. We are both convinced that a scale-out, shared-nothing architecture — the foundation of Hadoop — is essential for IoT, data warehousing and ML. We have each innovated separately in those areas.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

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

JUNE 5, 2019

The sheer volume of data currently existing is huge enough without also grappling with the amount of new information that’s generated every day. Think about it: financial transactions, social media posts, web traffic, IoT sensor data, and much more, being ceaselessly pulled into databases the world over.

Big Data 75

Big Data Cost-Benefit IoT Structured Data 75

Cloudera

DECEMBER 15, 2017

Data volumes from both inside as well as outside the manufacturing process continue to grow. The makeup of data changes too, and is more and more unstructured. Getting a handle on these flows of information becomes cost prohibitive with the current approaches. A modern platform based on open source.

Manufacturing 40

Manufacturing Machine Learning IoT Data-driven 40

Cloudera

OCTOBER 17, 2023

As organizations shift from the modernization of data-driven applications via Kafka towards delivering real-time insight and/or powering smart automated systems, Flink At Current, adoption of Flink was a hot topic and many of the vendors (Cloudera included) use Flink as the engine to power their stream processing offerings as well.

Data-driven 79

Data-driven Enterprise IoT Data Warehouse 79

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. 4 Data and analytics leaders, CDOs, and executives will increasingly work together to develop creative ways for data assets to generate new revenue streams.

Analytics 40

Analytics IoT Internet of Things Machine Learning 40

Octopai

MAY 30, 2019

The Benefits of Structured Data Catalogs. At the most basic level, data catalogs help you organize your company’s massive datasets. Most enterprises have huge data lakes with millions of touchpoints all living in the dark.

Metadata 40

Metadata Data Governance Data Lake IoT 40

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 72

Cost-Benefit Internet of Things Enterprise Technology 72

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

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Yet another decade passed.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

FineReport

APRIL 11, 2023

Free Download of FineReport Benefits and limitations of Business Intelligence Dashboard (BI Dashboard) BI dashboards have become essential tools for enterprises to extract valuable insights from their expanding data repositories, which often encompass structured, unstructured, and semi-structured data.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Domino Data Lab

MARCH 3, 2019

There are essentially four types encountered: image/video, audio, text, and structured data. That’s most likely a mix of devops, telematics, IoT, process control, and so on, although it has positive connotations for the adoption of reinforcement learning as well.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

Sisense

JULY 23, 2021

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. The data flow consists of the following steps: The IoT simulator on Amazon EC2 generates continuous data streams.

Data Lake 94

Data Lake IoT Metadata Testing 94

AWS Big Data

OCTOBER 25, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Ravi holds dual Bachelors degrees in Physics and Electrical Engineering from Washington University, St.

Statistics 91

Statistics Data Warehouse Metadata Data Lake 91

Jet Global

MAY 9, 2024

Real-Time Analytics Pipelines : These pipelines process and analyze data in real-time or near-real-time to support decision-making in applications such as fraud detection, monitoring IoT devices, and providing personalized recommendations. As data flows into the pipeline, it is processed in real-time or near-real-time.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52