Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

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Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

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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.

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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

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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.

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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.

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Astera

APRIL 28, 2023

To address these challenges, approximately 44% of companies are planning to invest in artificial intelligence (AI) to streamline their data warehousing processes and improve the accuracy of their insights. AI is a powerful tool that goes beyond traditional data analytics.

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The BAWorld

SEPTEMBER 6, 2024

In today’s world data cleaning or data cleansing is crucial step in any data analytics practices. It has mainly focused on identifying the data errors, inconsistencies and inaccuracies in the data and make sure that is accurate, complete and reliable for data analytics.

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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.

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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

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.

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Astera

JANUARY 23, 2023

See how we can help Best Practices of Healthcare Data Management To maximize the potential of implementing a healthcare data management system, hospitals and other healthcare facilities must collaborate to effectively manage, organize, safeguard, and transfer patient and provider information. to analyze data.

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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.

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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.

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Astera

NOVEMBER 14, 2023

And consequently, having a constantly evolving architecture means you will have access to accurate, up-to-date data to fuel your analytics, allowing teams and departments to meet their respective goals.

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Astera

JANUARY 25, 2024

Operationalizing insights from stored data and making them actionable in day-to-day business operations. Use Cases Data warehousing, business intelligence, reporting, and data analytics. Data enrichment for CRM, targeted marketing campaigns, real-time customer interaction, and personalized experiences.

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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.

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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.

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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.

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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.

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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.

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Astera

AUGUST 28, 2024

However, with the abundance of different types of data analysis tools in the market, what was supposed to be a simple task has become a complex undertaking. This article aims to simplify the process of finding the data analytics platform that meets your organization’s specific needs.

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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.

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