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 Ingestion.

Big Data 100

Big Data B2B Cost-Benefit Structured Data 100

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. By decoupling storage and compute, data lakes promote cost-effective storage and processing of big data. Why did Orca choose Apache Iceberg?

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

AWS Big Data

OCTOBER 3, 2023

Over the years, data lakes on Amazon Simple Storage Service (Amazon S3) have become the default repository for enterprise data and are a common choice for a large set of users who query data for a variety of analytics and machine leaning use cases. Analytics use cases on data lakes are always evolving. Choose ETL Jobs.

Data Lake 98

Data Lake Metadata Snapshot Recreation/Entertainment 98

AWS Big Data

JUNE 7, 2023

For this, Cargotec built an Amazon Simple Storage Service (Amazon S3) data lake and cataloged the data assets in AWS Glue Data Catalog. They chose AWS Glue as their preferred data integration tool due to its serverless nature, low maintenance, ability to control compute resources in advance, and scale when needed.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

Jet Global

MAY 1, 2023

Data Environment First off, the solutions you consider should be compatible with your current data architecture. We have outlined the requirements that most providers ask for: Data Sources Strategic Objective Use native connectivity optimized for the data source. Do what you expect your customers to do.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52