Domino Data Lab

AUGUST 9, 2021

Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data. Based on the concept of neural networks, it’s useful for analyzing images, videos, text and other unstructured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Alation

JUNE 2, 2022

In part two of this series, I’ll dive more deeply into AI/ML and data lineage, in the cloud and otherwise, and discuss how data governance and security can support these critical use cases, wherever they reside. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

JUNE 28, 2022

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 132

Management Internet of Things Statistics Data-driven 132

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data mining 220

Data mining Data Collection Strategy Data Analytics 220

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

Smarten

MAY 17, 2017

Smart Data Visualization goes beyond data display to suggest options for visualization and plotting for certain types of data, based on the nature, dimensions and trends inherent in the data. What is the difference between viewing structured data and compiling and analyzing unstructured data?

Visualization 40

Visualization Business Intelligence Unstructured Data Interactive 40

Cloudera

NOVEMBER 25, 2020

In any pharma, one of the largest data problems is variety, and it has been unsolved for the last 11 years, because: . Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

CIO Business Intelligence

APRIL 4, 2023

Let’s look at the data architecture journey to understand why and how data lakehouses help to solve complexity, value and security. Traditionally, data warehouses have stored curated, structured data to support analytics and business intelligence, with fast, easy access to data. Want to learn more?

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

Cloudera

JULY 26, 2021

PoS and transaction data to optimize supply chain operations). A growing desire for self-service analytics among internal data consumers and knowledge workers, external partners and clients. hybrid or public, multi-cloud) and advanced analytical frameworks (e.g., data warehousing).

Strategy 114

Strategy Marketing Unstructured Data Data Science 114