The Boltic approach to solving your Big Data Ops problem is modern & comprehensive - to solve a bigger problem, Boltic breaks it down into smaller pieces transforms it ,and encompasses a series of actions in a pipeline(aka Bolt), which is governed and sharable. Let us understand how we do it by learning about Boltic's core concepts -
Let's Start with Bolt
A Bolt is the journey of integrating data from a source, applying transformations, to load into a destination.
No coding is required to integrate multiple data sources and bring them under one roof with Boltic Integration. This functionality allows you to create separate integrations for different data sources (SQL-based and NoSQL-based databases, Local Files, Datawarehouse, and Clouds). Other teammates will be able to reuse the integrations you create.
Once you add an integration, you may need to work on a particular data set. We refer to that smaller subset of the data as a 'Dataset.' A 'Dataset' is sliced & diced data from your 'Integrated' source. Datasets can be created by writing queries or by using the visual mode. For example, you can extract a piece of a dataset from the integrated data source and transform it by writing SQL statements or using the Visual mode to build SQL queries without coding. The dataset you will create can be saved and reused by the other teammates.
The datasets created using query and visual modes are pulled from raw data. There is no structure of the data at this stage. Using Transformation, you can clean, enrich and alter the datasets and bring them to the standard reporting formats.
Data that has been transformed and verified is now ready to be loaded into a destination. This is the last stage of a Bolt journey- the data you retrieved from a source and then transformed into a standard format will get sent to a destination (target repository), where users can access it for a variety of business objectives.
This shall give you a clear understanding of all the core concepts you need to know to create a Bolt.
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