Sisense
SEPTEMBER 3, 2019
This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP.
Argon Digital
AUGUST 11, 2022
From there they moved into client/server and then web-based enterprise document management systems (what we now refer to as enterprise content management systems), moving to their first web native solution with Documentum 4i in 2000, which integrated business process management with content management. Modern content management features.
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Sisense
FEBRUARY 24, 2021
In fact, in a 2019 edition of Industrial Management & Data Systems, a research team led by Yu Nie noted that prior to the year 2000, there were only six chief data officers in the world. Clearly, data is becoming more important to organizations. This is one approach to solving the challenge of data silos.
Insight Software
MAY 1, 2023
These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. If the app has simple requirements, basic security, and no plans to modernize its capabilities at a future date, this can be a good 1.0.
Insight Software
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.
Insight Software
AUGUST 27, 2021
Jet Analytics is a robust Business Intelligence (BI) solution that complements Jet Reports with a data warehouse and advanced analytics capabilities. It includes pre-built projects, cubes, and data models, as well as a suite of ready-to-run reports and dashboards. We designed Jet Analytics for operational efficiency.
Insight Software
FEBRUARY 23, 2024
This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application.
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