MicroStrategy and its Business Intelligence Capability

MicroStrategy Incorporate, or MSTR, is an Enterprise Business Intelligence application software vendor. It has analytics and reporting tool that is highly capable. The company has been around since 1989 as a data analytics business.

The platform has various features like interactive dashboards, superior report formatting, automated report distribution, etc. There are also different interfaces such as the web and desktop.

Architecture of MicroStrategy

What sets MicroStrategy apart is the use of relational OLAP architecture. Most similar companies use MOLAP or multidimensional OLAP architecture that supports summary-level report making. MicroStrategy also uses an Object Layer. It has a Metadata-driven architecture, a central repository that stores all the objects.

The single metadata structure allows consistency and easier maintenance. It has a 64-bit architecture that can support in-memory Analytics. It is a method of querying data available in the computer’s RAM. In MicroStrategy, it is done with the help of Intelligence Cube. This means the OLAP reports are cached in the memory as data sets. 

The metrics and attributes are created once and are used across the different types of reports. The platform’s structure enables making changes in one place, and all the relevant reports get updated automatically. The same applies to security permissions. As a result, the administrative costs are reduced.

Object Layer Model

MicroStrategy comprises four layers of objects- Administration objects, Report Objects, Analysis objects, and Schema Objects.  The layers store all the objects that are created in the MicroStrategy Metadata.

Administration Objects

This layer comprises security, performance parameters, and user grouping. All of these, put together, govern the MicroStrategy applications. All these are objects for managing MicroStrategy users. 

It includes an option for user authentication, which is the basic security before allowing a user into the MicroStrategy environment. The user groups are used to make a collection of users to whom specific privileges are assigned. User privileges let them use only specific subsets of the features available. The user permission is there to prevent or grant access to certain objects.

Report Objects

These objects include a dashboard, enterprise reports, cross-tabs, and graphs. These assemble all the building blocks from the Schema and analysis object layer. As a result, you experience an insightful textual and visual analysis derived from these objects.

It also comprises the objects which form a report. This means it has objects like attributes, metrics, custom groups, and consolidations. They can be dragged and dropped from the report layout as required to add or remove data.

The report objects can be varied and depend on the type of report being made.

Analysis Objects

This layer makes all kinds of sophisticated analysis of the reports possible. The Analysis layer consists of objects developed on the schema layer. Objects like templates, metrics, command prompt, filters, custom groups, and consolidation are part of this layer.

Schema Objects

The primary feature you get is a logical abstraction of the database schema for various business models. These are tailormade for the business, thus, providing a customized solution. The objects included are tables, facts, hierarchies, transformation, and attributes.

ROLAP Model

Unlike the conventional OLAP/MOLAP model, the ROLAP model offers a much more detailed reporting of the entire relational database. It allows the user to access more profound levels of data way down to the transaction level. This tool is helpful in analyzing, optimizing, and accessing high-end data across all multidimensional databases, including flat files. 

Dynamic MDX Engine

Dynamic MDX Engine is one of the three major components of the ROLAP model. With it, you can generate Multidimensional Expressions or MDX and optimize it. MDX is a query language used in analytical processing. It is similar to SQL, and the syntax is the same as spreadsheet formulas. 

MDX can be considered an extension of SQL and can be used to access data stored in SQL Server cubes. This helps accumulate dimensional facts better from SAP, Hyperion Essbase, Microsoft Analysis Services, etc. 

Dynamic SQL Engine

This programming methodology is used for creating and optimizing SQL statements. With it, you can write flexible programs for general purposes with ease. This is very useful in accessing data warehouses more interactively. 

Dynamic SQL is needed where SQL cannot support your operation. With its help, you can find the exact SQL statements required for performing the PL/SQL procedure. Various factors affect this, like user input and program processing.

Freeform SQL Engine

Speaking of flexibility, Freeform SQL lets you utilize your own SQL statements. This allows you to create your own reports instead of using the ones generated by the MicroStrategy Engines. The best part about this is that you can use the reports created from Freeform SQL in all Developer and Web functions of MicroStrategy. 

Thanks to the Freeform SQL Engine, you gain direct access to the operational databases. This includes spreadsheets, graphical Query Builders, and even text files. You also have the option to choose previously created SQL statements for reference when creating Freeform SQL reports or start from scratch. 

Unified Metadata Model

Last but not the least, in MicroStrategy Architect, you can develop multiple sources as a single data source. This is important for easily accessing the information later and acting as a warehouse for them as unified metadata. Every template, report, facts, and metrics ever created, executed, or collected through the previous models can be stored here. 

The UMM or Unified Metadata Model offers a guideline for mapping. It is necessary for achieving consistent, relevant, and actional control over the data ecosystem of an enterprise. It prevents your organization from making costly decisions based on the wrong data.

This includes:

• Good Metadata Management
• A Metadata Strategy
• Capture and Storage
• Integration and Publication

Conclusion

Having a proper strategy while searching and drilling across data in a rational database is the primary focus of MicroStrategy. It allows for a more singular, cohesive approach that empowers enterprises and business owners to use their data efficiently.