Octopai

APRIL 19, 2021

Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. Strong metadata management enhances business intelligence which leads to more informed strategy and better performance. Donna Burbank.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

FineReport

APRIL 26, 2023

Unlike traditional databases, processing large data volumes can be quite challenging. With Big Data Analytics, businesses can make better and quicker decisions, model and forecast future events, and enhance their Business Intelligence. How to Choose the Right Big Data Analytics Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. The raw data can be fed into a database or data warehouse. An analyst can examine the data using business intelligence tools to derive useful information. .

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

DataKitchen

OCTOBER 11, 2021

Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes.

Testing 152

Testing Metadata Dashboards Statistics 152

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. Free Download.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

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. There are a wide variety of data pipelines that can be used in different industries and contexts.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52