Data Analytics enables enterprises to deep dive into their data to make accurate, timely decisions that optimize processes, enhance profitability, and manage risk.

The earliest application of data analytics was limited to applying basic statistics to data. But, the times have changed, so has the analytics industry. Today, businesses across geographies are leveraging advanced statistical analytics and machine learning models to drive enterprise-wide strategies.

As Analytics potentially impacts multiple functions within an organization, setting up data analytics solutions requires a full-fledged business strategy and commitment. GrowthLyne has successfully designed such analytics roadmaps and delivered integrated analytics solutions for many organizations. Clients have leveraged our expertise across many business processes and diverse industries.

Organizations can drive their successful analytics strategy where business goals have efficient technological support. Therefore, it is imperative for large and medium enterprises, to integrate their ETL tools that organize and store data with subsequent technologies which use this data for advanced analytics. GrowthLyne has successfully partnered with clients to design such seamless solutions. 

GrowthLyne experts can create the ETL architecture using a broad set of tools like Oracle, Informatica, IBM, Pentaho, etc which can create an integrated data architecture for both structured and unstructured data. This data can then be utilized in an analytics framework. Our advanced analytics capabilities cover a wide range of machine learning and classical econometrics techniques. 

The GrowthLyne team has developed these advanced analytics models over multiple software tools such as Python, R, SAS, EViews, SPSS, and others. We have developed our proprietary libraries across these powerful tools, which enable faster and standardized model development and implementation. 

To explore more about our capabilities, reach out to us at