CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. It’s also handy for data scientists, working with smaller datasets.

Data Science 138

Data Science Statistics Machine Learning Visualization 138

FineReport

JUNE 24, 2021

Originally, Excel has always been the “solution” for various reporting and data needs. However, along with the diffusion of digital technology, the amount of data is getting larger and larger, and data collection and cleaning work have become more and more time-consuming. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

FineReport

FEBRUARY 5, 2020

Overall, as users’ data sources become more extensive, their preferences for BI are changing. They prefer self-service development, interactive dashboards, and self-service data exploration. To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department.

Metadata 98

Metadata Dashboards Informatics Visualization 98

FineReport

MARCH 7, 2024

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. User Analysis If we delve into the core of big data analysis, it lies in user analysis.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Cloudera

AUGUST 20, 2021

Legal and Regulatory Requirements: CDP delivers data products to address complex and continuously evolving legal and regulatory requirements by offering a programmatic way to dynamically manage data permissions at a granular level by type of data asset and for different roles / users interacting with and manipulating those data assets. .

Strategy 96

Strategy Cost-Benefit Visualization Data Warehouse 96

Timo Elliott

JANUARY 22, 2019

Compliance drives true data platform adoption, supported by more flexible data management. As it has been for the last forty years, data collection, preparation, and standardization remain the most challenging aspects of analytics. Traditional analytics focused on structured data flowing from operational systems.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

datapine

NOVEMBER 19, 2019

This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience. Thus, deep nets can crunch unstructured data that was previously not available for unsupervised analysis. Voice-as-User Interface (VUI).

Technology 279

Technology Internet of Things IT IoT 279

IBM Big Data Hub

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Architecture 61

Data Architecture Data Lake Machine Learning Data Governance 61

AWS Big Data

FEBRUARY 1, 2024

Set up Athena to run interactive SQL. It includes massive amounts of unstructured data in multiple languages, starting from 2008 and reaching the petabyte level. Despite the original C4 data being part of Common Crawl, Meta opted for the reprocessed version of this data. Create an EMR Serverless environment.

Metadata 99

Metadata Modeling Data Processing Unstructured Data 99

datapine

FEBRUARY 22, 2022

Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Rely on interactive data visualizations.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Jet Global

MAY 9, 2024

By processing data as it arrives, streaming data pipelines support more dynamic and agile decision-making. Here’s how a streaming data pipeline typically works: Data is ingested continuously from one or more sources, such as sensors, log files, user interactions, IoT devices, social media feeds, or other real-time data streams.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

FEBRUARY 21, 2023

SQL Depth Runtime in Seconds Cost per Query in Seconds 14 80 40,000 12 60 30,000 5 30 15,000 3 25 12,500 The hybrid model addresses major issues raised by the data vault and dimensional model approaches that we’ve discussed in this post, while also allowing improvements in data collection, including IoT data streaming.

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67