Business Intelligence

Based on the analytics platform of Microstrategy

Microstrategy is a top independent analytic software vendor in the world with a comprehensive suite designed for team, departmental, and enterprise analytical use cases

Microstrategy is an organically developed unified architecture based on common metadata(semantic graph) avoiding the effort to integrate various products usually as a result of different vendor acquisitions

With its Enetrprise Semantic Graph, Microstrategy automatically generates queries that can blend data from multiple sources.( support more than 200 out of the box data connectors to market-leading providers)
and providing Reusability (easy to develop), Robust security, Ease of administration, Enterprise scalability, Lower cost of ownership

Self service BI and Governed data discovery

Business Users Today Want Direct Access To More Data as they are getting more involved in producing analytical content. To make insightful decisions on their own, business users demand instant access to Data from multiple enterprise sources and adopting Self-service Analytics By Business Users to Increase Productivity

Microstrategy allows users to seamlessly report, analyze, and monitor data across multiple sources through a single multi-dimensional view of the business. which brings the need for a modern data architecture including various types of data and thus the need for a Data Lake: – A storage repository, usually in Hadoop, that holds a vast amount of raw data in its native format until it is needed Contains a mix of structured, semi-structured and unstructured data.

Data warehouse

The Data Warehouse is the foundation for Business Intelligence

Data Warehouse and Business Intelligence terms together refer to the delivering of the entire end to end solution from the source extracts to the queries and applications that the business users interact with.

The creation of a high quality data source referred to as a “single version of the truth and to facilitating data Governance and regulatory compliance has always been what data warehousing stands for

Technically Data Warehouse provides separate data for  querying and analysis from the data for transaction processing as the first need to be structured around business terms and model that make sense to the business user.

Traditionally Data Warehouse is modelled around so called Subject areas via star schema or normalize relational database design

Data Vault

In recent years a third so called hybrid approach is emerging called the Data Vault

According to Dan Linstedt father of the Data Vault approach  , “The Data Vault is a detail oriented, historical tracking and uniquely linked set of normalized tables that support one or more functional areas of business. It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star schema.”

The Data Vault 2.0 approach simplifies data ingestion from multiple sources, makes it easy to add new data sources without disruption, and increases scalability and consistency.

In order to understand the requirements for building a data warehouse an iterative approach through building and analyzing prototypes needs to be applied.

Building datawarehouse prototypes quickly and populating them with data enhances the capability to understand the  requirements for building and delivering successful BI/DWH projects which makes data automation tools necessary.

Wherescape is a data warehouse automation tool  made to specifically address the need to Design, Prototype(build and document) Deploy and Maintain(operate and enhance) the Data warehouse fast.

Cloud and the Data Lakehouse

As cloud technology starts to prevail more data warehouse are being implemented in the cloud with vendors like Snowflake, Amazon Redshift and Teradata

Scalability of Cloud technology a new paradigm for storing structured and unstructured data aka Big Data emerge for analysis – Data Lakehouse  provide a persistent staging area capturing a superset of the data being fed to the Data warehouse.

Data Lakehouse is a hybrid storage based on open source technology like SPARK  and Apache Parquet such as Delta Lake from Databricks that aim to integrate both worlds