Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data analytics case study: SkullCandy.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

FineReport

JUNE 24, 2021

Once the data becomes more extensive or more complex, Excel or other simple solutions may “fetter” your potentialities. That’s why business intelligence solutions(BI solutions) come into our minds. Business Intelligence Solutions Definition. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 93

Data Warehouse Data Lake Analytics Data Science 93

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 105

Data Lake Unstructured Data Data Warehouse Data Quality 105

FineReport

DECEMBER 27, 2021

Modern enterprise business intelligence (BI) tools and practices enable quick decision making. Indeed, Early action on insights allows businesses to identify internal trends and improve inefficiencies. Furthermore, It is important to note that the advantages of business intelligence vary by industry and application.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

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

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. This design philosophy was adapted from our friends at Fishtown Analytics.).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CDW Research Hub

APRIL 28, 2020

Automate data loads with job scheduling so that your data is always there when you need it. Quickly access data for business intelligence, reporting and visualization, or access next-generation analytics platforms like ThoughtSpot. Use Matillion’s universal REST API to connect to any AP-enabled application.

Data-driven 52

Data-driven Analytics Consulting ROI 52

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 90

Data Lake Data Warehouse Data-driven B2B 90

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. 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