Why Lyftron

We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems.

Shorten Time to Insights

Experience collaborative data modelling, self-service data preparation and instant logical data warehousing to deliver business intelligence in real-time. Data preparation with Lyftron starts with real-time access to selected sources and the legacy data warehouse from one place.

After transformations are applied, the data is bulk loaded to the new database of the users choice. The technology’s logical data warehouse layer provides parallel access to both data warehouses and all data
sources in one place.

Enterprise-Wide Data Catalog and Data Lineage

Enables full database objects search guided by the principles of tagging, alias, and data set definition. Lyftron’s platform empowers data analysts to collaborate with ease. The data lineage process is also simplified, enabling teams to bring in visibility for data sets usage on various stages and maintain a healthy warehouse.

Hybrid Cloud Management and Migration

Build a hybrid cloud data warehouse that acts as a data bridge between leading cloud platforms, on-premise data warehouses and data sources. With Lyftron, users can access all the data from different regions in a data hub instantly and migrate from legacy databases to a modern data warehouse without worrying about coding data pipelines manually.

The data loading part should be responsible for keeping the data synchronized across databases, while the data bridge would let BI tools execute SQL queries across the cloud boundary.

Dynamic And Flexible Data Transformation Process

With the cutting edge ELT processes, you can virtually connect to any type of data source and ingest to your data warehouse without worrying about structure or schema.

Data Pipelines Modeled Around Agility And Flexibility

Lyftron offers highly flexible data pipelines that scale automatically along with the surge in the data and offer you highly flexible solutions that quickly adapt to the changes in your data landscape.

Realtime Access To All Your Data Sources

With real-time access to your data, monitor the changes happening in your data environment and take timely actions. Empower analysts and business leaders with comprehensive business intelligence to take quick and well informed business decisions.

Hot topics on BI journey


Large, complex, and rapidly changing datasets require complex processing techniques to handle. That is where Big Data starts. The digital world is generating huge amounts of data in all aspects of our life eg. IoT, smart home, smart cities, e-commerce, omnichannel etc. For businesses, becoming more and more data-driven is a must to keep up and gain a competitive advantage. Big Data analytics lets business users make smart decisions based on ubiquitous data.

Real time access

Real-time access brings an instant view on real data from source systems. No need to wait for capturing, processing and data aggregation. We live in a fast-paced environment where latency is unacceptable in a decision making process. Smart decision must be made promptly to get ahead of the concern.

Agile BI​

Agile BI is a groundbreaking view of Business Intelligence. The new idea of BI development biased towards rapid adaptation to business changes. It turns BI classical approach upside down. It shifts an effort from data sourcing to data modeling and provides more self-service for business analysts. Agile BI brings empowerment for business analysts, shorter development cycles, lower development costs, faster feedback and more.

Separation of data model and presentation

When data structure for reporting is centrally defined, tangible benefits occur. In a data-driven world, people count on reporting, collaborate and make collective decisions. They need freedom of choice: where, when and how they get access to data. Separation of the data model and presentation tools makes it all possible lowering the costs of implementation and ensuring data governance at the same time.