Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

The BAWorld

NOVEMBER 22, 2021

Top Data Analytics terms are explained in this article. Learn these to develop competency in Business Analytics. Data Analytics Terms & Fundamentals. Conformity is a data quality dimension, and it measures how well the data aligns to internal, external, or industry-wide standards.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. Both approaches aim to improve data quality and enable accurate analysis.

Data Warehouse 208

Data Warehouse Data Quality Data Analytics Data Analytics 208

Astera

DECEMBER 21, 2022

These data warehouses leverage the power of the cloud to offer enhanced scalability, flexibility, and elasticity to organizations. Today, more and more businesses are adopting cloud data warehouses as part of their data analytics and business intelligence strategies, owing to the benefits they offer.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Marutitech

JANUARY 21, 2022

Data science management has become an essential element for companies that want to gain a competitive advantage. The role of data science management is to put the data analytics process into a strategic context so that companies can harness the power of their data while working on their data science project.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

Insight Software

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models.

Data Management 95

Data Management E-Commerce Data Analytics Data Analytics 95

Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage.

Data Quality 96

Data Quality Government Artificial Intelligence Data Warehouse 96

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? The overarching goal of this architecture is to provide a robust foundation for analytical processing.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? The overarching goal of this architecture is to provide a robust foundation for analytical processing.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

APRIL 7, 2023

A robust data warehouse architecture does everything in data management—including ETL (extraction, transformation, loading)—while ensuring data quality, consistency, speedy retrieval, and enhanced security at all times. Improving Data Quality and Consistency Quality is essential in the realm of data management.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

AUGUST 22, 2023

Uncover hidden insights and possibilities with Generative AI capabilities and the new, cutting-edge data analytics and preparation add-ons We’re excited to announce the release of Astera 10.3—the the latest version of our enterprise-grade data management platform.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

DECEMBER 22, 2022

It’s one of the three core data types, along with structured and semi-structured formats. Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. This makes managing unstructured data difficult.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

OCTOBER 27, 2023

Practical Tips To Tackle Data Quality During Cloud Migration The cloud offers a host of benefits that on-prem systems don’t. Here are some tips to ensure data quality when taking your data warehouse to the cloud. The added layer of governance enhances the overall data quality management efforts of an organization.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Cprime

MAY 4, 2023

Key Data Integration Use Cases Let’s focus on the four primary use cases that require various data integration techniques: Data ingestion Data replication Data warehouse automation Big data integration Data Ingestion The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Actian

JUNE 4, 2019

Data Migration – If you are replacing an existing data warehouse or consolidating data from your current databases, then you will need to migrate data from the old systems into the new warehouse. The migration itself isn’t difficult, but this is often when you discover data quality issues that must be addressed.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40

Astera

APRIL 24, 2024

Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. Interactive, Automated Data Preparation : Ensures data quality using data health monitors, interactive grids, and robust quality checks.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52