Organization refers to the people part of the enterprise and the part that I consider most important in the DG journey. This is the “Who” part of the framework. The success of any efforts including data governance is based on the readiness of the organization.
The need of Data Governance has been established at it has become one of the key initiative’s organizations are focusing on when it comes to managing the data. This blog talks about the differences in the Data Governance in Digital era when it compares to traditional Data Governance practices.
Changing business models, technology democratization, security and increasing digital assets have made data governance need of the hour. This blog establishes a framework and the components that organizations can use to start or improve the DG efforts.
Data governance is a discipline of data management which deals with understanding the data assets, securing the data and managing the data. The field has been around as long as people have been using data, however the need of the data governance has become far more important in this digital era.
Three popular Data processing architecure for big and small data on cloud. These cover various scenarios for both batch, realtime, small and big data. The links take to the dedicated blog for each architecture
In this section we go Azure Databricks and create the cluster and notebook to ingest the data in real-time and process and visualize the stream
Databricks is becoming the new normal in data processing technologies in cloud, both Azure and AWS. This is step by step guide to get started on Realtime (streaming) analytics using spark streaming on Databricks
Delta architecture processes any new streaming records like delta (incremental) records and data lake is no longer immutable data structure
When we see entities in real world, we notice that there is a complex relationship occurs between the entities. Every entity type is unique and has multiple possible relationships. Graph databases solve this problem by providing ways to model the relationships in the database and that makes the insights very simple and easy
The key steps organizations can take to cross that hurdle/chasm and move ahead of the roadblock and prepare the foundation which will enable them to move along the curve