- [[Types|Types of data]]
- [[Storage Comparison]]
- [[Data Warehouse]]
- [[LakeHouse|Data Lake(house)]]
- [[Modelling]]
- [[Processing]]
- [[StructuralQueryLanguage|Data Query Language]]
- [[Semantic layer]]
- [[Visualization]]
- [[Business Intelligence]]
- [[Data Science]]
- [[Machine Learning]] / [[Artificial Intelligence]]
- [[Natural Language]]
- Data: apply meaning
- Information: apply context
- Knowledge: apply insight
- Wisdom: apply purpose
- Decission
40 Key Computer Science Concepts Explained In Layman’s Terms How To Reduce the Costs of Database Management in Financial Services mysql - Relationship between catalog, schema, user, and database instance - Stack Overflow
- [[#Embedded analytics]]
- [[#Distributed analytics]]
technology designed to make data analysis and business intelligence more accessible Embedded analytics - Wikipedia What Is Embedded Analytics? | Reveal Business Intelligence Glossary
- one data analytics team that takes care about preparing insights and dashboards over data
- people come to ask and rely on this team
- parallel need - more people to see some kind of analytics (external/internal)
- information needed to be shared across organization
- BI tools needed to shift to something that is useful and customizable by different types of
- businesses
- semi-technical users
- someone who understands the data on the architecture level (know SQL, how to query)
- rest of people are preparing parts of end-user analytics (the name distrbuted)
- responsibility to connect the physical data from their sources into so called semantic model
- building analytics easily by drag&dropping, even without SQL knowing code or understanding the data
- guarantee to see data dedicated to specific users
- play with it
- data needs to be shared across different strucutre (granularity and hierarchy -huge and varies)
- same mechanisms underneath but people see just relevant data