Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. It helps organizations understand trends, patterns, and anomalies in their data.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. Business intelligence (BI) platforms. The rise of cloud computing and cloud data warehousing has catalyzed the growth of the modern data stack.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

MAY 11, 2023

With the “Data Productivity Cloud” launch, Matillion has achieved a balance of simplifying source control, collaboration, and dataops by elevating Git integration to a “first-class citizen” within the framework. In Matillion ETL, the Git integration enables an organization to connect to any Git offering (e.g.,

ETL 52

ETL Analytics Analytics Data Modeling 52

IBM Journey to AI blog

JULY 3, 2024

To power AI and analytics workloads across your transactional and purpose-built databases, you must ensure they can seamlessly integrate with an open data lakehouse architecture without duplication or additional extract, transform, load (ETL) processes.

AI 45

AI AI Data Quality Database 45

phData

OCTOBER 11, 2023

KNIME Analytics Platform is an open-source data analytics tool that enables users to manage, process, and analyze data. Microsoft Power BI has established itself as a premier data visualization product used to turn unrelated data sources into coherent, visually immersive, and interactive insights.

Power BI 59

Power BI Data Preparation Data Warehouse Analytics 59

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

phData

JULY 18, 2023

Slow Response to New Information: Legacy data systems often lack the computation power necessary to run efficiently and can be cost-inefficient to scale. This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data.

Data Warehouse 52

Data Warehouse Analytics Analytics SQL 52