Astera

OCTOBER 25, 2023

Data transformation is a process that can help them overcome these challenges by changing the structure and format of raw data to make it more suitable for analysis. This improves data quality and facilitates analysis, enabling them to leverage more effectively in decision making.

Data Quality 52

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Astera

JANUARY 18, 2024

So, in case your data requires extensive transformation or cleaning, Fivetran is not the ideal solution. Fivetran might be a viable solution if your data is already in good shape, and you need to leverage the computing power of the destination system. Change data capture (CDC) for all relational databases in one platform.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

NOVEMBER 1, 2023

Data Integration: A data warehouse enables seamless integration of data from various systems and eliminates data silos and promotes interoperability and overall performance. Data-driven Finance with Astera Download Now Who Can Benefit from a Finance Data Warehouse?

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Astera

FEBRUARY 7, 2024

Moreover, highly complex data require more development and maintenance resources to maintain zero-ETL solutions. Compared to zero-ETL , traditional ETL is well-suited for complex data transformations and extensive preprocessing. and transformations during the staging phase.

Real-time Data 52

Real-time Data Cybersecurity Data Quality Monitoring 52

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). This presented the first challenge for our product team in building Cascade Insight: What is the data that is most important to capture?

Skillset 52

Skillset Data Requirement Data Quality Documentation 52

Astera

MAY 9, 2023

Data Quality While traditional data integration tools have been sufficient to tackle data quality issues, up till now, they can no longer handle the extent of data coming in from a myriad of sources.

Healthcare 40

Healthcare Retail Finance Data Quality 40

Astera

MAY 25, 2023

As such, it is critical for businesses and organizations to not only collect and store big data, but also ensure its security to protect sensitive information and maintain trust with customers and stakeholders. In this blog, we will discuss the importance of big data security and the measures that can be taken to ensure it.

Big Data 40

Big Data Data Security Monitoring Data Quality 40

Astera

MAY 4, 2023

This, in turn, enables businesses to automate the time-consuming task of manual data entry and processing, unlocking data for business intelligence and analytics initiatives. However , a Forbes study revealed up to 84% of data can be unreliable. Luckily, AI- enabled data prep can improve data quality in several ways.

Business Intelligence 40

Business Intelligence Business Intelligence Predictive Analytics Supply Chain 40

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

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

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Astera

APRIL 29, 2024

How are the data quality issues identified and resolved within the strategy? Why is a Data Governance Strategy Needed? IDC predicts that by 2025, the worldwide volume of data is expected to expand by 163 zettabytes, covering information across physical systems, devices, and clouds.

Data Governance 52

Data Governance Government IBM Maintenance 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

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

MARCH 26, 2023

But managing this data can be a significant challenge, with issues ranging from data volume to quality concerns, siloed systems, and integration difficulties. In this blog, we’ll explore these common data management challenges faced by insurance companies.

Documentation 52

Documentation Data Quality Data Warehouse Data Management 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

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. It provides a strategic framework to manage enterprise data with the highest standards of data quality , security, and accessibility.

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

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

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.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

Astera

MAY 26, 2023

On average, it took the retailer 15 days (about 2 weeks) to process the invoices—from data extraction to payment. Consequently, the inefficient process was time-consuming and error-prone, causing delays in account payables, data quality discrepancies, and supply-chain disruptions.

Retail 40

Retail Supply Chain Finance Data Quality 40

Astera

SEPTEMBER 20, 2023

Data Movement Data movement from source to destination, with minimal transformation. Data movement involves data transformation, cleansing, formatting, and standardization. Data Quality Consideration Emphasis is on data availability rather than extensive data quality checks.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Data Movement Data movement from source to destination, with minimal transformation. Data movement involves data transformation, cleansing, formatting, and standardization. Data Quality Consideration Emphasis is on data availability rather than extensive data quality checks.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 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

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

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

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

Astera

JANUARY 12, 2024

Self-Serve Data Infrastructure as a Platform: A shared data infrastructure empowers users to independently discover, access, and process data, reducing reliance on data engineering teams. However, governance remains essential in a Data Mesh approach to ensure data quality and compliance with organizational standards.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Data Pine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

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? Ensure Data Governance Check for compliance with relevant data protection regulations.

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