Astera

APRIL 28, 2023

Final Verdict: Intelligent Systems are Changing the Game Intelligent systems are revolutionizing data management by providing new and innovative ways to analyze, process, and interpret vast amounts of data. Serving as a unified data management solution.

Data Management 93

Data Management Artificial Intelligence Predictive Analytics Data Quality 93

Sisense

FEBRUARY 10, 2021

In order to do this, my team uses data to identify problem areas and potential issues for our customers (ideally before they happen). Utilities employ skilled professionals as knowledge workers, but creating a simple, visual way to analyze their data is a hard skillset to find in abundance.

Skillset 52

Skillset Data Requirement Data Quality Documentation 52

Astera

JULY 20, 2023

Best Practices for Successful EDI Mapping To achieve the most seamless interoperability capabilities and maximize the benefits of utilizing EDI tools, businesses can adhere to key best practices that ensure efficient mapping processes and optimal data compatibility.

Supply Chain 52

Supply Chain Documentation Digital Data Requirement 52

Astera

DECEMBER 21, 2022

Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance. Fortunately for forward-thinking organizations, cloud data warehousing solves many of these problems and makes leveraging insights quick and easy. What is a Cloud Data Warehouse?

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Astera

MAY 6, 2024

Type of Data Mining Tool Pros Cons Best for Simple Tools (e.g., – Data visualization and simple pattern recognition. Simplifying data visualization and basic analysis. – Steeper learning curve; requires coding skills. Can handle large volumes of data. Data quality is a priority for Astera.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

FEBRUARY 9, 2024

Financial data integration faces many challenges that hinder its effectiveness and efficiency in detecting and preventing fraud. Challenges of Financial Data Integration Data Quality and Availability Data quality and availability are crucial for any data integration project, especially for fraud detection.

IBM Support 52

IBM Support Data Quality IBM Maintenance Data Governance 52

Astera

MARCH 19, 2024

It involves developing and enforcing policies, procedures, and standards to ensure data is consistently available, accurate, secure, and compliant throughout its lifecycle. At its core, data governance aims to answer questions such as: Who owns the data? What data is being collected and stored?

Data Governance 52

Data Governance Government Data Quality Monitoring 52

Astera

MARCH 11, 2024

According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. Unsurprisingly, businesses are already adopting Snowflake ETL tools to streamline their data management processes.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Astera

OCTOBER 12, 2023

The platform also allows you to implement rigorous data validation checks and customize rules based on your specific requirements. Furthermore, by providing real-time data health checks, the platform provides instant feedback on the data quality, enabling you to keep track of changes.

Data Quality 52

Data Quality Monitoring Real-time Data Government 52

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units. Intended Use of Data.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units. Intended Use of Data.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

JANUARY 9, 2023

With the advancements in cloud technology, a single cloud provider can easily fulfill all data requirements. Moreover, you should have complete data visibility to carry out a meaningful analysis. Data Quality. Let’s delve into the details. Why Multi-Cloud Strategy Makes Sense?

Data Quality 52

Data Quality Data Requirement Visualization Data Management 52

Astera

DECEMBER 7, 2023

Compliance and Regulatory Reporting In industries subject to stringent regulations like finance and healthcare, batch processing ensures the consolidation and accurate reporting of data required for compliance. This includes generating reports, audits, and regulatory submissions from diverse data sources.

Supply Chain 52

Supply Chain E-Commerce Data Warehouse Real-time Data 52

Astera

DECEMBER 7, 2023

Compliance and Regulatory Reporting In industries subject to stringent regulations like finance and healthcare, batch processing ensures the consolidation and accurate reporting of data required for compliance. This includes generating reports, audits, and regulatory submissions from diverse data sources.

Supply Chain 52

Supply Chain E-Commerce Real-time Data Data Warehouse 52

Data Pine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

Astera

APRIL 24, 2024

They gather, process, and analyze data from diverse sources. From handling modest data processing tasks to managing large and complex datasets, these tools bolster an organization’s data infrastructure. What are Data Aggregation Tools?

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Astera

APRIL 29, 2024

Did you know data scientists spend around 60% of their time preprocessing data? Data preprocessing plays a critical role in enhancing the reliability and accuracy of analytics. This blog will discuss why data preprocessing is essential for making data suitable for comprehensive analysis.

Big Data 52

Big Data Retail Healthcare Finance 52