AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

FineReport

APRIL 11, 2023

In today’s fast-paced business environment, making informed decisions based on accurate and up-to-date information is crucial for achieving success. With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Jet Global

SEPTEMBER 4, 2020

Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of business objects within the database, such as, customers, general ledger accounts, or purchase orders.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

MARCH 26, 2024

The following diagram shows a sample C360 dashboard built on Amazon QuickSight. You can benefit from its ML integrations for automated insights like forecasting and anomaly detection or natural language querying with Amazon Q in QuickSight , direct data connectivity from various sources, and pay-per-session pricing.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84