datapine

JUNE 5, 2019

Without the existence of dashboards and dashboard reporting practices, businesses would need to sift through colossal stacks of unstructured data, which is both inefficient and time-consuming. In doing so, your business will be data-driven, and as a direct result – more successful. How Data Dashboards Are Used In BI.

Dashboards 316

Dashboards KPI Sales Visualization 316

datapine

JUNE 9, 2022

Data monitoring has been changing the business landscape for years now. That said, it hasn’t always been that easy for businesses to manage the huge amounts of unstructured data coming from various sources. By the time a report is ready, the data has already lost its value due to the fast-paced nature of today’s context.

Dashboards 143

Dashboards Metrics Visualization Sales 143

Smarten

JUNE 10, 2022

Traditional business intelligence is focused on reporting and queries, whereas advanced analytics is focused on the analysis of structured and unstructured data to optimize, correlate and predict the activities and strategies that will help the business succeed and to predict results. Business Intelligence. Dashboards.

Slice and Dice 52

Slice and Dice Analytics Key Performance Indicator Business Intelligence 52

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

Cloudera

AUGUST 16, 2021

Hundreds of built-in processors make it easy to connect to any application and transform data structures or data formats as needed. Since it supports both structured and unstructured data for streaming and batch integrations, Apache NiFi is quickly becoming a core component of modern data pipelines.

Dashboards 119

Dashboards Metrics KPI Data-driven 119

FineReport

FEBRUARY 5, 2020

To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis. Management, security and architecture of the BI platform.

Metadata 98

Metadata Dashboards Informatics Visualization 98

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57