Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse ETL Cloud Data Tableau 52

ODSC - Open Data Science

FEBRUARY 24, 2023

Its goal is to help with a quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst. You can watch it on demand here.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 3, 2023

What is Business Intelligence? Business Intelligence (BI) refers to the technology, techniques, and practises that are used to gather, evaluate, and present information about an organisation in order to assist decision-making and generate effective administrative action. billion in 2015 and reached around $26.50

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. The dedicated data analyst Virtually any stakeholder of any discipline can analyze data.

Data Science 77

Data Science Analytics Analytics Data Scientist 77

IBM Journey to AI blog

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52