Name: The technology behind DataVirtuality
Uploaded: 2015-07-23T14:36:26.000Z
Duration: 1 min 3 s
Description: The technology behind DataVirtuality

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Transcription

Professional Services

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Headless eCommerce

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Sales

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Security Information and Event Management (SIEM)

Security

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### Data Integration
Users have highlighted Data Virtuality's data integration capabilities as a key factor in optimizing their processes and enhancing data accessibility. The platform's ability to easily integrate data from various sources, coupled with its efficient ETL processes, has been praised for streamlining operations and improving data management. Additionally, the SQL editor has proven to be a valuable tool for data discovery and modeling, enabling users to derive insights and offer personalized services to clients. The platform's support for real-time data access and its compatibility with different databases, APIs, and files have further solidified its position as a reliable data integration tool in the eyes of users.

### Data Virtualization
Users' experiences with Data Virtuality's data virtualization capabilities seem to be diverse. While some users praise its efficiency in managing data from various sources and providing quick access, others may have encountered challenges or limitations. The platform's ability to integrate data through JDBC and REST API connectors into a centralized virtual layer appears to be a key feature appreciated by users. However, the extent to which it meets the specific data needs of different teams and the ease of use may be areas where opinions differ.

### Data Science and Analytics
Users have consistently praised Data Virtuality Platform for its robust data science and analytics capabilities, emphasizing its role in streamlining data transformation processes and enabling the derivation of valuable insights from multiple data sources. The platform's support for custom queries and data modeling has proven instrumental in enhancing the efficiency and effectiveness of data analysis and reporting tasks.

### SQL and Querying
Users widely praise Data Virtuality Platform for its robust SQL capabilities and advanced querying functionalities. The platform's SQL editor is particularly highlighted for its ease of use and effectiveness in transforming data and schemas. Reviewers appreciate the intuitive setup of Pipes and the affordability it offers while providing an integrated SQL editor for easy ETL processes. Despite some users mentioning the need for better onboarding materials and SQL skills, the overall sentiment leans towards positive experiences with Data Virtuality Platform's SQL and querying features.

Extensive library of connectors: Many users have found the extensive library of connectors provided by Data Virtuality to be very helpful, with multiple reviewers mentioning this as a positive aspect. This wide range of connectors allows users to easily integrate various data sources into their workflows and saves them time on integration efforts.

Powerful SQL engine for customization: The powerful SQL engine of Data Virtuality has been praised by several users. They appreciate the ability to completely customize the data flow from sources to various data tools, which provides greater flexibility in data management. This feature has been highly regarded by multiple reviewers.

Real-time data access and simplified retrieval: Several users have mentioned that Data Virtuality's capability to enable real-time data access from any source is a valuable benefit. By treating all sources as SQL databases, this feature enhances data accessibility and simplifies the process of retrieving required information. Multiple reviewers have highlighted this aspect as a positive attribute of Data Virtuality.

Complex Server Administration: Some users have found the administration of the server to be complex, requiring the use of scripts instead of a GUI. This has made it challenging for them to navigate and manage the system efficiently.

Lack of Onboarding Materials: Several reviewers have noted that onboarding materials and best practices are lacking, making it necessary to have good SQL skills and knowledge of databases in order to be productive right away. This lack of guidance has caused some frustration for new users.

Difficulty Understanding Data Sources: Users have expressed the need to know the data dictionaries in order to understand all the sources. Without this information readily available, it can be time-consuming and confusing for them to analyze and interpret the data effectively.

Users highly recommend trying out Data Virtuality during the 14-day test phase to experience how it effectively centralizes data. They also suggest considering data virtualization, specifically Data Virtuality, for faster data delivery and efficient management in organizations. Another recommendation is to take advantage of the product trial and utilize the support chat option for any issues or questions, as users have found the support to be excellent. Overall, users are very satisfied with Data Virtuality, appreciating its sophisticated software with a wide range of features that have successfully supported building marketing analytics stacks and improving infrastructure.

The Data Virtuality Platform is a data integration and management solution designed to integrate data from various sources, regardless of type, format, or location. According to the vendor, this platform targets small to large enterprises and is suitable for data architects, data engineers, business analysts, heads of data, and DevOps professionals. It finds applications across industries such as e-commerce/retail and financial services, offering a unified data access layer and streamlining data integration processes.

## Key Features

**Connect**: According to the vendor, the platform enables the integration of data from disparate sources using methods like data virtualization, ETL/ELT, streaming, and CDC.

**Query**: The platform allows users to create a central data logic using SQL language for data queries, simplifying data integration and enabling the retrieval of specific information from multiple sources.

**Replicate**: The platform seamlessly replicates data using SQL commands translated into native data source commands, supporting real-time replication from various sources into a centralized data repository.

**Deliver**: According to the vendor, the platform facilitates the delivery of data to any data consumer, supporting integration with a wide range of tools and applications, and providing flexibility in delivering data in various formats and programming languages.

**Data Governance**: The platform offers robust data governance features, including data quality controls, access controls, and compliance with data regulations and standards, to ensure data integrity, security, and compliance.

**Business Data Shop**: The platform provides a centralized data marketplace for users to discover and access pre-integrated data sources, streamlining the data discovery and access process while promoting collaboration and knowledge sharing.

**Security, Authentication, Audit**: According to the vendor, the platform implements security measures, authentication mechanisms, and auditing capabilities to protect data, control access, and ensure compliance with data security and privacy regulations.

**Change Data Capture (CDC)**: The platform captures and replicates only changed data in real-time, supporting incremental updates and enabling efficient and timely data replication for near-real-time analytics and reporting.

**Optimization**: The platform optimizes data integration and query performance through query optimization techniques, caching mechanisms, and tools to enhance the overall data integration workflow, according to the vendor.

**Streaming**: According to the vendor, the platform supports real-time data streaming, enabling the integration of streaming data sources into the data integration pipeline and facilitating the processing and transformation of streaming data in real-time.

Data Virtuality, headquartered in Leipzig, offers two products to solve data integration and management problems in a tailored way that best suits data teams in the fast-paced world of data. The Data Virtuality Platform combines data virtualization and data replication, Data Virtuality Platform provides data teams the flexibility to always choose the right method for the specific requirement. It is an enabler for Data Fabric and Data Mesh by providing the  self-service capabilities and data governance features that support these frameworks.

Data Virtuality Platform

Data virtualization tools provide a virtual abstraction layer for multiple sources of data without copying or moving the data. This layer hides the technical aspects of stored data like location, structure, access language and storage technology. Data virtualization tools allow many different data sources to act as a single, consistent source for data consumers.

Data Virtualization

Data Virtuality: The World of Data Virtualization Podcast

Likelihood to Recommend

Data Virtuality

The technology behind DataVirtuality

The Logical Data Warehouse can connect to over 100 data sources to analyze any of your data with a front-end of your choice.

This is possible without classical ETL and a combination of data virtualization and our analytical storage.

Learn more at http://www.datavirtuality.com/

Data Visualization

Data Visualization software features help clients and businesses better visualize and present data.

Data Visualization Options

Provides a wide range of customizable data visualization options such as charts, graphs, maps, and tables to effectively present data.

Interactivity

Enables users to interact with the visualizations by clicking, hovering, zooming, or filtering to explore the data further.

Data Import and Export

Allows users to easily import data from various sources like databases, spreadsheets, CSV files, and APIs, and export visualizations for sharing or further analysis.

Dashboard Creation

Allows users to create interactive dashboards by combining multiple visualizations and data components into a single layout for a comprehensive view of data.

Customization Capabilities

Offers options to customize colors, styles, labels, fonts, and other design elements to tailor visualizations to specific needs and branding.

Data Filtering and Sorting

Enables users to filter and sort data within visualizations based on specific criteria to focus on relevant information and trends.

Project Collaboration Tools

Provides features for multiple users to collaborate on data visualizations simultaneously, share insights, and work on projects together.

Real-time Data Updates

Supports real-time data streaming and updates to ensure that visualizations reflect the most current information and changes.

Cross-platform Accessibility

Allows users to access and view data visualizations on different devices and platforms such as desktops, tablets, and smartphones.

Data Analytics Integration

Integrates with data analytics tools and platforms to perform advanced data analysis, derive insights, and enhance visualization capabilities.

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Jr. Data Analyst

Data Virtuality Platform 2022-11-02 16:42:38

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Data Virtualization Tools

We use Data Virtuality, a fantastic concept that simplifies
mapping data structures to relational tables. It's brilliant to use a few lines
of SQL to connect to SFTP Server, query new JSON files, convert them to XML,
and map all acquired data to the relational model for the warehouse. About 20
lines of clean, well-structured SQL code are needed. There are pipes in place
for each potential data source. Pipes was the only option we found that met our
requirements, as it was both reasonably priced and included an integrated SQL
editor, making ETL a breeze. I like data replication and stored procedures
language (more than T-SQL)—customer support is excellent. If there's a bug,
they fix it quickly and send us the patch. Thus, I have a fair opinion of the
Data Virtuality Platform.

ETL/ELT model building is flexible.
The pipes' setup and use are intuitive.
It lets us access various data sources, extract, and analyze data.

Configuring data connectors can be tricky.
Price could be more flexible and adapt to the use case.
The ETL builder's user interface could be prettier.

Data accessibility.
Rapid prototypes of BI.
Centralized business logic data.
Stored procedure data flow automation.

It has the capability of integrating data from a variety of different sources.
It improved development and user interface to offer a robust MDM repository and strategy.
It offers a comprehensive solution for processing and retrieving data, which is one of the ways it assists.

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Data Virtuality Platform

Overview

What is Data Virtuality Platform?