Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

APRIL 28, 2023

By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations. For instance, Coca-Cola uses AI-powered ETL tools to automate data integration tasks across its global supply chain to optimize procurement and sourcing processes.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

APRIL 23, 2024

Data quality metrics are not just a technical concern; they directly impact a business’s bottom line. million annually due to low-quality data. Furthermore: 41% of data warehouse projects are unsuccessful, primarily because of insufficient data quality.

Data Quality 52

Data Quality Monitoring Data Modelling Data Warehouse 52

Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. 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.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. 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.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

APRIL 7, 2023

Finally, the stored data is retrieved at optimal speeds to support efficient analysis and decision-making. Essentially, a data warehouse also acts as a centralized database for storing structured, analysis-ready data and giving a holistic view of this data to decision-makers.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Actian

FEBRUARY 25, 2020

The IT industry is changing rapidly, and there are 4 key emerging technology trends that data management and IT professionals should be monitoring closely. From a data management perspective, this raises the need to manage data in motion (traveling between apps over APIs) as well as data at rest (within individual applications).

Data Warehouse 40

Data Warehouse Data Management Data Modelling Monitoring 40

Sisense

JULY 14, 2019

As indicated above, a robust, ISO-compliant analytics platform delivers data security and fine-grained access control, as well as encryption and authentication methods. Admins should be able to programmatically apportion user access by group, team, or individual, by data model, dataset, or down to the individual row-level.

Data Security 75

Data Security Data Modelling Documentation Cybersecurity 75

Data Pine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business.

Data Quality 96

Data Quality Monitoring Big Data Government 96

Actian

JUNE 4, 2019

Implementing a data warehouse is a big investment for most companies and the decisions you make now will impact both your IT costs and the business value you are able to create for many years. Data Warehouse Cost. Your data warehouse is the centralized repository for your company’s data assets.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40

Sisense

MAY 27, 2019

As more and more data warehousing moves to the cloud, engineers increasingly find themselves working with AWS cloud services, EC2, EMR, RDS, and Redshift, other cloud-based data warehouses such as Snowflake and Google BiqQuery, cloud computing services like Microsoft Azure, and data orchestration systems such as Kubernetes.

Skillset 75

Skillset Cloud Computing Big Data Visualization 75

Smart Data Collective

JUNE 16, 2022

Data is fed into an Analytical server (or OLAP cube), which calculates information ahead of time for later analysis. A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on. An OLAP system cannot access transactional data.

Data Warehouse 324

Data Warehouse Data Modelling Monitoring Business Intelligence 324

Astera

MAY 30, 2024

Variability: The inconsistency of data over time, which can affect the accuracy of data models and analyses. This includes changes in data meaning, data usage patterns, and context. Visualization: The ability to represent data visually, making it easier to understand, interpret, and derive insights.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Astera

SEPTEMBER 1, 2023

The significance of data warehousing for insurance cannot be overstated. It forms the bedrock of modern insurance operations, facilitating data-driven insights and streamlined processes to better serve policyholders. The data warehouse has the highest adoption of data solutions, used by 54% of organizations.

Data Warehouse 40

Data Warehouse Data Modelling Data Security Data Quality 40

Astera

JANUARY 24, 2024

Modern data management relies heavily on ETL (extract, transform, load) procedures to help collect, process, and deliver data into an organization’s data warehouse. However, ETL is not the only technology that helps an enterprise leverage its data. The tool offers open-source extensibility.

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Astera

JANUARY 31, 2024

Its extensibility is evident through components, such as SQL Server Integration Services (SSIS) for ETL , SQL Server Reporting Services (SSRS) for creating and managing reports, SQL Server Analysis Service (SSAS) for analytical data models, and so on. Azure SQL Database).

Data Warehouse 52

Data Warehouse Visualization Data Management Data Quality 52

Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Remember to monitor and validate your data to ensure it remains accurate, complete, and relevant.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Tableau

APRIL 18, 2022

Review quality and structural information on data and data sources to better monitor and curate for use. Data quality and lineage. Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Data modeling. Data preparation.

Data Quality 99

Data Quality Government Artificial Intelligence Data Warehouse 99

Tableau

APRIL 18, 2022

Review quality and structural information on data and data sources to better monitor and curate for use. Data quality and lineage. Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Data modeling. Data preparation.

Data Quality 97

Data Quality Government Artificial Intelligence Data Warehouse 97

Astera

JANUARY 2, 2024

Free Download Here’s what the data management process generally looks like: Gathering Data: The process begins with the collection of raw data from various sources. Once collected, the data needs a home, so it’s stored in databases, data warehouses , or other storage systems, ensuring it’s easily accessible when needed.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Sisense

JUNE 26, 2019

We have often talked about the single-stack approach to business analytics, and with the complexity of enterprise data, this approach makes even more sense. . You want to make sure you have one place to bring in all your data and do your data modeling. In this case, you may want to connect live to these sources.

Data Warehouse 75

Data Warehouse Data Modelling Big Data Monitoring 75

Astera

JUNE 3, 2024

Data warehouses Data warehouses are a specialized type of database designed for a specific purpose: large-scale data analysis. Data needs Data structure: Analyze the type of data the organization needs to store—structured, semi-structured, or unstructured. Ready to try Astera?

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 52

Astera

JUNE 14, 2023

Centerprise : It is user-friendly software that smoothly integrates data from various sources. You can design, execute, and monitor data integration workflows with this tool. It supports different data formats and offers features like data profiling, cleansing, mapping, and transformation to ensure high-quality data.

Procurement 52

Procurement Data Security Retail Monitoring 52

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Talent Acquisition 96

Talent Acquisition Data Warehouse Data Architecture Visualization 96

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Talent Acquisition 94

Talent Acquisition Data Warehouse Data Architecture Visualization 94

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

AUGUST 22, 2023

This new addition allows you to evaluate and compare models, fine-tune parameters, and ensure accuracy and relevance—all within a unified environment. Astera Data Analytics offers built-in performance monitoring, reporting, and experimentation capabilities, providing transparency and rapid prototyping.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

MARCH 28, 2024

Additionally, data catalogs include features such as data lineage tracking and governance capabilities to ensure data quality and compliance. On the other hand, a data dictionary typically provides technical metadata and is commonly used as a reference for data modeling and database design.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Salesforce Data Cloud for Tableau solves those challenges.

Talent Acquisition 53

Talent Acquisition Data Warehouse Data Architecture Visualization 53

Cprime

JANUARY 27, 2021

At the heart of the Power Platform is Microsoft’s Common Data Model (Service). The CDS is a data storage service in Microsoft 365. Power BI is a set of services, apps, and connectors that together turn your unrelated sources of data into coherent, virtually immersive, and interactive insights.

User Experience 52

User Experience Documentation Data Warehouse Visualization 52

Whizlabs

JUNE 15, 2021

4D: Data-driven Development. The future is going to be data-driven development, where it’ll not just be enough to make an app or software, but you will also have to create a data model and manage the data amongst your users. . As per your own terms, you can also monitor the metrics.

Cloud Computing 52

Cloud Computing Data Warehouse Data Modelling Monitoring 52