The volume of data has grown dramatically over the years, and organizations have realized that insights from data are their biggest assets. Despite the emergence of Big Data Analytics, AI & Machine Learning, and other modern technologies, traditional data warehouse, business intelligence and reporting constitutes a major chunk of workloads. Whether it is retail, insurance, finance, or manufacturing, DW/EDW and BI remains a powerful tool for data analytics, reporting, and visualization. Optigrise follows a unified approach to data engineering using unified tools and processes, extending DevOps & Agile principles to data
- Solid Approach – Separate tools, process for different teams
- Separate Pipelines – Separate pipeline/data flow b/w traditional data engineering, big data & ML teams.
- Focus on data science only – While AI and predictive analytics solve many use cases, still organisations have huge amount of data in relational and structured form, they should continue to have a strong DW/BI strategy.
- Unified Approach – Unified tools, process
- Unified Pipelines – Unified pipeline from data ingestion, data preparation to visualization for traditional DW/BI, Big data & AI.
- Balanced Approach – Balanced approach b/w traditional DW/BI, Big data & AI.
- Data Ops – Bringing in Devops & Agile Principles to data projects.
- Cost Optimization – Cost saving on DW/BI, so that additional savings could be spent on AI & Big data.