A foundation for better decisions 
for data engineers
                        As a modern data solution, Lyftrondata addresses the evolving need of data-driven enterprises and provides a sophisticated architecture designed to improve the efficiency and effectiveness of data engineers.
The fastest way to 
 data, growth, and decisions
                    Data engineers oversee exponential measures of quickly evolving data. They center around the advancement, arrangement, the board, and enhancement of data pipelines and framework to transform and transfer data to data scientists for querying. Lyftrondata enables data engineers or analysts to blend any data with an automatic data pipeline in minutes, not months, analyze it instantly with ANSI SQL, visualize it with any BI tool and share it with confidence.
We make BI and big data analytics work easier and faster. Lyftrondata gives you a central view of data from multiple data sources to build a modern data pipeline and replication on the fly, along with advanced security, data governance, and transformation with simple ANSI SQL. With features such as these, we empower business users and heavily loaded BI specialists to be less dependant on each other when solving data-driven business problems.
Eliminate the complexity with Lyftrondata's simplicity
Velocity 2000+
Parallel auto data migration jobs
Speed 
75%
                                    Faster results to insights
Cost 
60%
                                    Reduction in 
cost
Time 
200X
                                    Faster 
migration
Density 
100X
                                    Faster business 
decisions
Simplicity 
1500X
                                    Faster 
learning
Agile-based modern architecture for
flawless data engineering
                        
                    
                        Instant data access
Lyftrondata’s technology combines the columnar data pipeline process with modern data hub architecture that eliminates traditional extraction, transformation and loading (ETL)/ extraction, loading and transformation (ELT) bottlenecks with automatic data pipelines. This makes data instantly accessible to BI users with the power of Spark and Snowflake.
                        Improved collaboration
Lyftrondata connectors automatically convert any source into the normalized, ready-to-query relational format and provide search capabilities on enterprise data sets to improve collaboration and enable early access to all data in one, central location.
                        Save cost and time
The platform provides a view of all data in one place without data movement and enables governed data lake and cloud data warehousing. This functionality, and the ability to prototype data models in real-time, results in significant time and cost savings, while also improving scalability.
                        Excellent business outcomes
With Lyftrondata engineers are able to search and analyze data in real-time, and then use their favorite analytics tools to obtain results. They spend more time analyzing data and less time searching for it. Shorten time-to-insights by 75%.
                        Efficient data management
Lyftrondata manages a Data Pipeline that unifies all data sources to a single format and loads the data to a target Data Warehouse, which is used by BI tools. Go beyond simple data profiling to examine data and manage large data volumes at an unprecedented low cost. Quickly relate to the new data sets to meet growing business requirements.
                        Agile, flexible and adaptable
Get assurance that you can sync and access your real-time data in sub-seconds using any BI tool you like. Universal Data Catalog Tag-Based Search enables users to have full control of their data catalog and do the search with ease.
                    
                    
                    
                    
                    
                    
                    
                    
                    
                    
                    
                    
                                                







