Remove Big Data Remove Data Processing Remove Digital Transformation Remove Structured Data
article thumbnail

How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. Big data and data warehousing.

article thumbnail

Introduction To The Basic Business Intelligence Concepts

datapine

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Query the data using Athena Athena is a serverless, interactive analytics service built to analyze unstructured, semi-structured, and structured data where it is hosted. To query the data with Athena, complete the following steps: On the Athena console, open the query editor.

article thumbnail

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Spark SQL is an Apache Spark module for structured data processing. To run HiveQL-based data workloads with Spark on Kubernetes mode, engineers must embed their SQL queries into programmatic code such as PySpark, which requires additional effort to manually change code. Amazon EMR on EKS release 6.7.0 or later installed.

article thumbnail

The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.

article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. The following diagram shows the high-level data platform architecture before the optimizations.