Usual practice is to run the analytics on the final data available in the target platform. The trustworthiness of the numbers displayed in the dashboards would still be a question for the leadership team unless strict guidelines and practices with respect to data validations and reconciliations are implemented during the process of ETL data pipeline building. Quality data is critical to understanding any business operation. Data collected and reported after the transformation process can help organizations understand how well their data is converted into information assets and also helps the business teams to identify the issues and to take those suggestions back to IT teams to readjust the pipelines.

The use of reporting and analytics can provide significant benefits to keep tracking Key Performance Indicators (KPIs) and companies can ensure that their objectives are met. Reporting and analytics can also help businesses make more informed decisions. Additionally, analytics can help companies track customer behavior, profitability etc. before, during, and after major events, seasonal changes and several other unforeseen circumstances.

When it comes to making informed and intelligent business decisions, nothing is more important than having access to accurate and timely data. Reporting and analytics can help you do just that by giving you a clear view of how your business is performing at any given time. With this information, you can identify areas where you need to make changes to improve your bottom line. By having a clear picture of where your business stands, you can make the necessary adjustments to stay on track.

With the Dextrus data-driven approach, analytics are brought early into the ETL pipeline phass, so that the data is enriched at each stage and layer of data integration and transformation. The Analytics all the way approach helps the data practitioners build more efficient pipelines while leveraging this capability at every hop of the data’s journey in the pipeline. So, in addition to the usual approach of after the fact analytics, providing the flexibility of analyzing and visualizing the data during the pipeline configuration stage itself can bring huge positive impact on building more effective ETL pipelines. Additional features include real-time data analysis capabilities, connecting various working environments through one interface, and creating an embedded visualization component for building custom dashboards with ease and access to historical data.

Companies miss out on opportunities to improve customer service when not utilizing these tools. Without analyzing historical data, organizations may be limiting themselves from stopping potential problems from happening in the future and restricting their maximum sales and ROI. Harnesses the power of big data with reporting analytics, so you gain valuable insights into how your business is performing and operating with better efficiency and effectiveness. Enabling your business to improve customer service, increase revenue and generate overall performance improvements for your organization's operation.

Dextrus is a comprehensive data platform with components like ETL pipelines, Analytics, and Job scheduling. In addition to these Dextrus also has Data Wrangling component and ML Predictive Modeling components.