Smart Data Collective

NOVEMBER 18, 2020

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?

Data mining 143

Data mining Data Science Informatics Statistics 143

Jen Stirrup

OCTOBER 30, 2022

What distinguishes Data Mining from other methods of exploring data, and what is its usefulness? Critics might say that if you torture the data enough, it will eventually confess! Computers contain lots of data, but people need help to turn this data into intelligence.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

Jet Global

JUNE 5, 2019

So how does a leading-edge business find a way to marry their wealth of data with the opportunity to utilize it effectively via BI software? Let’s introduce the concept of data mining. Toiling Away in the Data Mines. Clustering helps to group data and recognize differences and similarities.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 135

Data mining Data-driven Statistics OLAP 135

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

CIO Business Intelligence

DECEMBER 22, 2022

DataOps in practice To make the most of DataOps, enterprises must evolve their data management strategies to deal with data at scale and in response to real-world events as they happen, according to Dunning and Friedman. They also note DataOps fits well with microservices architectures.

Analytics 129

Analytics Machine Learning Software Data Quality 129