Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

MAY 25, 2023

However, to ensure the effectiveness of these measures, businesses should regularly update and monitor these measures. Regular Audits and Risk Assessments Regular audits and risk assessments can help businesses identify vulnerabilities in their big data infrastructure. Encrypting data in transit (emails, file transfers, etc.)

Big Data 40

Big Data Data Security Monitoring Data Quality 40

Astera

JANUARY 25, 2024

Reverse ETL combined with data warehouse helps data analysts save time allowing them to focus on more complex tasks such as making sure their data is high quality, keeping it secure and private, and identifying the most important metrics to track. Data Models: These define the specific sets of data that need to be moved.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Sisense

JANUARY 14, 2021

Because of how delicate customer relationships can be, Billie expended considerable resources monitoring reported data for accuracy and fixing broken charts and reports before consumers could be affected. We believe this can help teams be more proactive and increase the data quality in their companies,” said Ivan.

E-Commerce 85

E-Commerce Business Intelligence Business Intelligence Data Modelling 85

Astera

JANUARY 23, 2023

Evaluate medical practitioners’ performance Data-based performance management involves evaluating the performance and attitudes of doctors and healthcare personnel to ensure standards for quality care are met. Ensuring Data Quality Medical errors are the third leading reason for death in the US.

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

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

Tableau helps strike the necessary balance to access, improve data quality, and prepare and model data for analytics use cases, while writing-back data to data management sources. Analytics data catalog. Data quality and lineage. Data modeling. Metadata management.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Tableau

APRIL 18, 2022

Tableau helps strike the necessary balance to access, improve data quality, and prepare and model data for analytics use cases, while writing-back data to data management sources. Analytics data catalog. Data quality and lineage. Data modeling. Metadata management.

Data Quality 96

Data Quality Government Artificial Intelligence Data Warehouse 96

Astera

JANUARY 24, 2024

Key Features of Astera It offers customized data quality rules so you can get to your required data faster and remove irrelevant entries more easily. It has orchestration features for scheduling, logging and monitoring, and error handling. Airbyte offers built-in scheduling, orchestration, and monitoring.

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Marutitech

JANUARY 21, 2022

Hence, if they are provided with the manager role, they will skimp on data science management. . What is the CRISP-DM Process Model? One of the essential tasks of data science management is ensuring and maintaining the highest possible data quality standards. Why Do You Need It? . Integrate ethics into everything.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

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

FEBRUARY 16, 2024

It facilitates the seamless collection, consolidation, and transformation of data from diverse sources and systems into a unified and standardized format. The advantages of this integration extend beyond mere organization; it significantly improves data quality and accuracy.

Finance 52

Finance Banking Data Quality Artificial Intelligence 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? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

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? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 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

Astera

JANUARY 2, 2024

Securing Data: Protecting data from unauthorized access or loss is a critical aspect of data management which involves implementing security measures such as encryption, access controls, and regular audits. Organizations must also establish policies and procedures to ensure data quality and compliance.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

SEPTEMBER 1, 2023

Data Integration: A data warehouse supports data integration across various subsidiaries, systems, and data formats, fostering interoperability and reducing data silos. Fraud Detection & Prevention Using Data Warehouse Utilizing a data warehouse, insurance companies can improve their fraud detection process.

Data Warehouse 40

Data Warehouse Data Modelling Data Security Data Quality 40

Astera

JUNE 14, 2023

Transformation: Converting data into a consistent format for easy use. Aligning external and internal data formats. Handling inaccurate and abnormal data. Ensuring data quality and consistency. Loading/Integration: Establishing a robust data storage system to store all the transformed data.

Procurement 52

Procurement Data Security Retail Monitoring 52

Astera

JULY 13, 2023

MDM ensures data consistency, reduces duplication, and enhances data quality across systems. It is particularly useful in scenarios where data integrity, data governance, and data quality are of utmost importance, such as customer data management, product information management, and regulatory compliance.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

AUGUST 22, 2023

Grid View: The Grid View presents a dynamic and interactive grid that updates in real time, displaying the transformed data after each operation. It offers an instant preview and feedback on data quality, helping you ensure the accuracy and integrity of your data.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 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.

Data Warehouse 52

Data Warehouse Visualization Data Management Data Quality 52

Astera

MAY 26, 2023

It includes support for grouping, sorting, and filtering data, as well as running mathematical and statistical operations. Data validation: MongoDB allows for the validation of data before it is inserted into the database. Therefore, ensuring data quality and consistency across the application.

E-Commerce 40

E-Commerce Documentation Data Security Data Quality 40

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

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

At its core, Astera boasts a potent ETL engine that automates data integration. Additionally, the platform’s customizable automation enhances efficiency by scheduling tasks and providing real-time monitoring to address integration errors quickly. These features streamline data integration, ensuring users enjoy uninterrupted data flow.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Insight Software

SEPTEMBER 1, 2023

These include data privacy and security concerns, model accuracy and bias challenges, user perception and trust issues, and the dependency on data quality and availability. Data Privacy and Security Concerns: Embedded predictive analytics often require access to sensitive user data for accurate predictions.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52