Data Virtualization with Lyftrondata a game changer and revenue generator
Data Virtualization with Lyftrondata empowers users to integrate data from disparate sources, provides greater flexibility in data access, limit data silos, and automates query execution for faster time-to-insight. Leverage data virtualization to complement processes like data warehousing, data preparation, data quality management, and data integration.
The modern data virtualization for greater speed, agility and response time
“Through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture.” Gartner Market Guide for Data Virtualization, 16 November 2018.
With Lyftrondata’s ultimate data virtualization architecture in place, users could perform data replication and federation in a real-time format, allowing for greater speed, agility, and response time. It enables effective data mining, predictive analytics, machine learning, and artificial intelligence.
The Data Virtualization Market size is forecast to reach $ 8.39 billion by 2025 growing at a CAGR of 20.6% during the forecast period 2020-2025.
Eliminate the complexity with Lyftrondata's simplicity
How it works
Data Virtualization (DV) enables Logical Data Warehouses(LDW). Data virtualization tools offer users a single interface — often based on SQL — to access data in multiple places or formats.
The LDW technology that resides in Lyftrondata allows a new approach and flexibility when it comes to managing data lakes. It is even possible to dispense with them due to the capacity of an LDW to contact the source directly in real-time and without any intermediaries. Why build a data lake if we can develop and model directly using data sources?
Lyftrondata integrates data virtualization, manages the unified data for centralized security, and delivers real-time data for best class performance. Lyftrondata provides a common abstraction over any data source type, shielding users from its complexity and back-end technologies it operates on. It relies on views that allow users to integrate data on the fly.
Get started in minutes, not months with these agile steps. Zero coding & zero setups required.
Integrate your data with Lyftrondata instantly and blend with 150+ other sources
Data extraction with Lyftrondata is easy. Be up and moving in minutes. Without any help from developers, Lyftrondata enables you to choose your most valuable data and pulls it from all your connected data sources in just a few click.
Empower your analytics with out-of-the-box relational data model
Once the data is extracted, you could ingest it to the data warehouse or BI tool of your choice with zero coding required. Lyftrondata connectors automatically convert any source data into a normalized structure of ANSI SQL and push down the data pipeline processing as an ELT to the native cloud data warehouse.
Built for the agile data culture for your data
Run SQL queries and virtualize your data instantly.
Analyze your data from any BI/ML tools
Data sharing is data caring
Define, categorize and find all data sets in one place. Share these data sets with other experts with zero code and drive better insights and user experience. This data sharing ability is perfect for companies who want to store their data once, share it with other experts and use it multiple times, now and in the future. We build the best data sharing process around your data stack. So say goodbye to the complex API, FTP and Email manual data sharing processes and simply onboard your consumers to the Lyftrondata platform in just a few minutes.
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Schedule a free, no-strings-attached demo to discover how Lyftrondata can radically simplify data lake ETL in your organization.
Know the heart and soul of data virtualization with Lyftrondata
What you get
Query API data with SQL familiar syntax
With Lyftrondata, avoid creating time-consuming code and use your very own SQL to query any data, both structured and semi-structured. Its modern data architecture supports automatic zero code JSON/XML/API parsing to relational format. Analyze instantly with ANSI and make your data lake work for you. Lyftrondata's emulation of Microsoft SQL Server allows any client supporting connectivity to SQL Server to connect to Lyftrondata.
Easily auto-extract JSON, XML schemas into relational format
No need to write any complex API, rest services, JSON, and XML parsing jobs. Lyftrondata takes care of all these, it converts any data into a relational format and, allows you to query it with simple ANSI SQL.
Emulation compatibility with SQL Server
- Metadata model exposed by SQL Server, including metadata catalog, system views, stored procedures, and functions.
- SQL dialect supported by SQL Server.
- Tabular Data Stream network protocol as described in Microsoft TDS documentation.
- Data types and conversions, where all data types are normalized automatically into equivalent SQL Server data types.
Secure your sensitive data with our encryption functions
Lyftrondata comes with a built-in enterprise data governance framework complying with all of the necessary rules and tools that your team needs to successfully operationalize your program. Amplify your information governance with a robust data lineage model that follows high-quality controls and governance mechanisms.
Perform complex transformations
Skip writing long complex APIs, and transform instantly with SQL. Define data transformations as a standard SQL. Lyftrondata pushes down SQL to data sources and the cloud, making it easy for all users to access the information they need in a timely fashion.
Quickly apply complex joins
Apply high cardinality joins between API sources, S3, Blob and database, without heavily relying on the BI and data engineering teams to set up complex and time-consuming ETLs.
Easily query data from S3, Blob, JSON, Xml like a table
Eliminate traditional ETL/EDW bottlenecks by auto- normalizing API/JSON/XML/S3/Blob/NoSql
sources into ready-to-query relational format. Focus on boosting the productivity of your data professionals and shorten your time to value.
Federate data sources like actual database
Take a leap from data federation technology and focus on performance optimization as well as self-service search and discovery. Spend more time analyzing data than searching for it.
State-of-the-art facial recognition API
Perform Azure cognitive AI access with our face recognition API function. Be on the top of technology, and use cognitive services that bring AI within reach of every developer—without requiring machine-learning expertise.
Emulation delivers compatibility with the following SQL Server features:
Lyftrondata easy-to-implement transformation functions supported for
Business benefits of data virtualization with Lyftrondata
An inside look of Lyftrondata
Data virtualization for all
Lyftrondata is a high-performance data virtualization solution for immediate data access, quick data centralization and data governance. Its next-gen architecture complements processes like data warehousing, data preparation, data quality management, and data integration for the highest possible performance.
It empowers enterprises to build a single source of data truth by using a virtual layer on their data environment, thereby providing real-time data access for faster decision making.
Architects could use this to abstract the complexity of accessing data and developers , to build applications quickly and easily, with zero coding environment.
Data virtualization with Lyftrondata makes the data available in minutes and automates data workflows using SQL, thereby cutting down the development, cost, time and efforts by 80%.
Focused on improved transparency and accountability, the modern architecture encapsulates critical information from the outside world and ensures users can’t change the data intentionally.
The modern data platform eliminates the time spent by engineers building data pipelines manually, and makes data instantly accessible by providing real-time access with simple ANSI SQL. Lyftrondata’s prebuilt connectors automatically deliver data to warehouses in normalized, ready-to-query schemas and provide full search on data catalog.
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