IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

JUNE 30, 2020

Data is usually visualized in a pictorial or graphical form such as charts, graphs, lists, maps, and comprehensive dashboards that combine these multiple formats. Data visualization is used to make the consuming, interpreting, and understanding data as simple as possible, and to make it easier to derive insights from data.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

JULY 26, 2021

A common pitfall in the development of data platforms is that they are built around the boundaries of point solutions and are constrained by the technological limitations (e.g., a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g., data warehousing).

Strategy 119

Strategy Data Science Unstructured Data Marketing 119

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 78

Management IT Machine Learning Metrics 78

Alation

JULY 19, 2022

In this way, a data scientist benefits from business knowledge that they might not otherwise have access to. The catalog facilitates the synergy of the domain experts’ subject matter expertise with the data scientists statistical and coding expertise. Modern data catalogs surface a wide range of data asset types.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

MARCH 27, 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. Complete the implementation tasks such as data ingestion and performance testing.

Testing 109

Testing Data Warehouse Metrics Cost-Benefit 109

FineReport

APRIL 11, 2023

Designed dashboards typically have the following components: Data Source Connections : BI dashboards can be connected to data warehouses, data marts, data lakes, operational systems, industrial equipment, and external data feeds to provide up-to-date and relevant information.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Data-driven 150

CIO Business Intelligence

APRIL 4, 2023

Let’s look at the data architecture journey to understand why and how data lakehouses help to solve complexity, value and security. Traditionally, data warehouses have stored curated, structured data to support analytics and business intelligence, with fast, easy access to data. Want to learn more?

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

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

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. Amazon Redshift has built-in autonomics to collect statistics called automatic analyze (or auto analyze).

Statistics 87

Statistics Data Warehouse Metadata Data Lake 87