Today’s data platforms are complex, dynamic environments critical to the success of your organization. Managing all the integrated components across the data lifecycle, from ingestion to visualization, has become increasingly difficult and costly. Most large data platforms consist of dozens of technologies, each requiring specialized skills to manage and support. Starschema’s managed data services ensure high availability and peak performance while reducing operational costs of your data pipeline.
Keeping your data platforms running with operational efficiency is both paramount and can be a costly and complicated endeavor. Join us and learn how to apply strategies, techniques, and tools to build a reliable and effective DataOps practice in your organization.
During this time of crisis, everyone is searching for answers. Governments, healthcare institutions, non-governmental organizations, and businesses large and small urgently need to make decisions about their future. We believe they should be armed with accurate, easily accessible, analytics-ready data. That’s why we collated, curated, and unified the most credible and reliable public data sets into a single source of truth data set.
In the age of artificial intelligence and machine learning, the standards for data quality have risen but machine learning can aid in cleansing and enriching data. In this webinar, Tamas Foldi, Starschema CTO and Tableau Zen Master presents the latest trends in data quality and enrichment and demonstrates how AI is helping to make cleaning and enriching data easier.
We design and implement data lakes to analyze data in distinct ways, gain insights and create value out of the data your organization generates and imports. Our standard BI Data lake solution implemented on Microsoft Azure platform is based on Lambda Architecture providing flexibility to process either structured data coming from traditional SQL databases or semi/non-structured data ingested from IoT devices, logs, documents.