AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. The Benefits of Structured Data Catalogs.

Metadata 40

Metadata Data Governance Data Lake IoT 40

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

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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