datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. They enable powerful data visualization.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). That’s how we got here.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

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

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. All BI software capabilities, functionalities, and features focus on data.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

FEBRUARY 20, 2024

The elasticity of Kinesis Data Streams enables you to scale the stream up or down, so you never lose data records before they expire. Analytical data storage The next service in this solution is Amazon Redshift, a fully managed, petabyte-scale data warehouse service in the cloud.

Visualization 102

Visualization Cost-Benefit Optimization B2B 102

CIO Business Intelligence

MAY 10, 2022

Customer data platform defined. A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Salesforce Interaction Studio. DMPs, however, use anonymized data.

Advertising 104

Advertising Interactive Marketing Data Integration 104

FineReport

APRIL 11, 2023

Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders. These dashboards are more interactive than traditional static reports, allowing users to access underlying data for further analysis.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. We have embedded LLMs in our Hue interface so you can write SQL queries in English or any other language.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

CDW Research Hub

DECEMBER 4, 2019

There are many benefits of using a cloud-based data warehouse, and the market for cloud-based data warehouses is growing as organizations realize the value of making the switch from an on-premises data warehouse.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

AWS Big Data

FEBRUARY 21, 2023

Business intelligence (BI) with dashboards, reports, and analytics remains one of the most popular use cases for data and analytics. It provides business analysts and managers with a visualization of the business’s past and current state, helping leaders make strategic decisions that dictate the future.

Visualization 52

Visualization Dashboards Data Warehouse Cost-Benefit 52

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML).

Data Lake 80

Data Lake Data Warehouse Sales Data-driven 80

AWS Big Data

MARCH 25, 2024

AWS Glue can interact with streaming data services such as Kinesis Data Streams and Amazon MSK for processing and transforming CDC data. With Amazon Managed Service for Apache Flink Studio , you can build and run Apache Flink stream processing applications using standard SQL, Python, and Scala in an interactive notebook.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

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. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52