AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

Management 79

Management IT Machine Learning Metrics 79

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

CIO Business Intelligence

DECEMBER 4, 2023

A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data. When data is stored in a modern, accessible repository, organizations gain newfound capabilities.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 58

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 58

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 74

Unstructured Data Data Architecture Data Lake Snapshot 74

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. Spreadsheets are not typically developed and managed for enterprise use, which opens the door to risk from malicious actors, as well as human errors.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

MARCH 26, 2024

Enrichment typically involves adding demographic, behavioral, and geolocation data. You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Sisense

JUNE 30, 2020

The data drawn from power visualizations comes from a variety of sources: Structured data , in the form of relational databases such as Excel, or unstructured data, deriving from text, video, audio, photos, the internet and smart devices.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. For Acast’s use case, granular row- or column-level access controls weren’t needed, so the approach sufficed.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

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

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

FineReport

APRIL 11, 2023

Additionally, they provide tabs, pull-down menus, and other navigation features to assist in accessing data. Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. to make better decisions and risk assessments.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61