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Core Concepts
The Modern Data Stack (MDS) is an ecosystem of data tools that emerged as a result of the rise of the cloud data warehouse.
For basic use cases, data teams can ingest data into a data warehouse, transform the data, visualize insights, and make informed decisions. Modern Data Stack also unlocks more complicated use cases, such as powering machine learning models, and real-time production systems.
The managed data stack made it easy for companies to create the data stack customized for their business needs. 5X platform integrates with the most reliable vendors in each category of the modern data stack, giving you the flexibility to choose the tools that best fit your business needs. You can build your stack by choosing the vendors you want for each category, or simply by taking our recommended templates based on industry and company size.
The Analytics Starter template provides the basic template to get you started. A typical data platform has the following 4 components:
- Data Ingestion (ETL/ELT): Extract data from databases and applications. Ingestions tools, such as Fivetran and Gravity, automate this ingestion process so you can move all of your data from sources to the data warehouse.
- Data warehouse: The one place to store your data from sources. The cloud data warehouse sits at the center of every data stack, in other words, you can’t build a stack without a data warehouse.
- Data transformation/modeling: The process of transforming raw data (such as cleaning data, changing structure, data type, and values), into analysis-ready data, which can be used as the single source of truth across the company. Transformation tools, such as dbt, also provide version control and structure complex query logic.
- Data Visualization/Business intelligence (BI): BI tools, such as Looker, Tableau, Sigma, Preset, and Metabase, allow companies to turn transformed data into visualizations and insights. These tools allow companies to easily explore their data and make data-driven business decisions.