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 68

Analytics Data Warehouse Data Lake Metadata 68

Jet Global

OCTOBER 2, 2019

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You can get faster insights without spending valuable time managing your data warehouse. Analyze the assessment report and address the action items.

Analytics 93

Analytics Data Warehouse Testing Dashboards 93

FineReport

JULY 16, 2021

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data analysis and processing can be carried out while ensuring the correctness of data. Data Warehouse. Data Analysis. REPORT FILLING.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

FineReport

JUNE 24, 2021

Data is the key to gaining great insights for most businesses, but it is also one of the biggest obstacles. Originally, Excel has always been the “solution” for various reporting and data needs. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Jet Global

OCTOBER 22, 2020

Power BI provides users with some very nice dashboarding and reporting capabilities. Unfortunately, it also introduces a mountain of complexity into the reporting process. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 52

AWS Big Data

JUNE 21, 2023

Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse. This dimensional model will be built in Amazon Redshift.

Data Warehouse 76

Data Warehouse Data Lake OLAP Cost-Benefit 76

Jet Global

MAY 28, 2019

The success of any business into the next year and beyond will depend entirely on the volume, accuracy, and reportability of the data they collect—and how well the business can analyze, extract insight from, and take action on that data. All About That (Data)Base. Enter the Warehouse.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Jet Global

SEPTEMBER 22, 2023

Dynamics ERP systems demand the creation of a data warehouse to ensure fast query response times and that data is in a suitable format for Power BI. The skills needed to create a data warehouse are currently in short supply, leading to long lead times, high costs, and unnecessary risks.

Visualization 52

Visualization Reporting Data Warehouse OLAP 52

Jet Global

MAY 1, 2023

But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. These reports are critical to making decisions.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52