The firm was founded in 1989 by Michael J Saylor, Sanju Bansal, and Thomas Spahr. It's a public company that provides business inteligence (BI), mobile software, and cloud-based services which develops software to analyze internal and external data in order to make the business decisions and to develop mobile apps.

Year by year, MicroStrategy has been developing, expanding and also improving their products and services. Here are some of the latest products that they improved and releases in the past 10 years from year 2020. They introduced MicroStrategy Mobile in 2010, which is a software platform that integrates analytics capabilities into apps that are available for iPhone, iPad, Android, and Blackberry. In year 2019, the prior platform release focused on 3 areas which are:

• Federated Analytics, allowing extended connectivity to data sourcesand applications.

• Transformational Mobility, for easier mobile application development.

• HyperIntelligence, integrating Bluetooth identity detection and voice.

In 2017, MicroStrategy 10.10 version were released. In MicroStrategy 10.10, they added MicroStrategy Workstation which uses business intelligence and predictive analytics to search through and perform analytics on big data from many kinds of data, including data warehouses, Apache Hadoop distributions, and Excel files. They didn't stop until year 2017, in year 2020 they releases it's business intelligence software that includes improvements to the vendor's HyperIntelligence Capabilities, an embedded analytics system using augmented intelligence and machine learning technology.

Until today, microstrategy are still developing their products to provide an advanced softwares that can be beneficial for the user in analysing data to make business decisions.

Since it has been mentioned before that MicroStrategy is used to analyze data, MicroStrategy has several features to accomplish that goal. Some of the features are:

• Data Discovery, which enables MicroStrategy to connect any data source and connect it from various sources (flat files, big data sources, social media platforms, and clous systems).

• Data Wrangling, which helps data transformation and modification with an extensive set of builtin data wrangling and parsing capabilities. These are history scripts that remember data transformations and can be reapplied to any analysis.

• Data Mining and Predictive Analysis, has a wide range of native analytical capabilities with the option to easily incorporate third-party data mining and modeling tools. The data mining service can be used to build predictive reports and distribute these reports to users on any devices.

• Library of Analytics Functions, it has an extensive library ober 300 OLAP, mathematical, financial, and data mining functions, that can be used to better understand the relationships between data, create business metrics and top-level KPIs, or building advanced statistical analyses.

• Extensible Visualization Library, has several features such as out-of-the-box grids, draphs, and in-built data visualizations tools. It also allows addition of hundreds of open-source visualization available from D3 or other providers with built-in tools that help with the integration process that also has a visualization builder and SK to code a new visualization from scratch.

• Real-time Dashboards, which is a feature that allows the user to build a dashboard that can source live data dashboard that provides live source data in a real-time monitoring of the current information. The dashboard will also have controllable intervals and the users can be guaranteed of the latest data.

• Embedded BI, which comes up with several out-of-the-box development-ready portlets that require no additional coding.

• Mobile Platform, the existing visualizations, reports, and dashboards are instantly available in mobile platform, once they are created.

SSMS is an integrated environment for managing any SQL infrastructure. SSMS is used to access, configure, manage, administer, and develop all of the components of SQL Server, Azure Synapse Analytics, and also Azure SQL Database. It also provides a single comprehensive utility that combines a broad group of graphical tools with a number of rich script aditors to provide access to SQL Server for developers and database administrator for all skill levels.

The SSMS also has a feature for non-english language version where the block on mixed languages set up has been lifted. The user can install SSMS German on a French windows. If the OS language doesn't match the SSMS language, the user needs to change the language by looking at these steps below:

Tools > Options > International Settings , if not SSMS will display the English UI.

SSMS can run on Windows (AMD or Intel) only. If the user needs a tool that can run on platforms other than Windows, the user needs to take a look at Azure Data Studio. The Azure Data Studio is a cross-platform toll that can run on macOS, Linux, as well as Windows.

• Business Intelligence

SSMS is used to access, configure, manage, and administer Analysis Services, Integration services, and Reporting Services, use SQL Service Management Studio.

• Managing Analysis Services Solutions

SSMS also enables the user to manage Analysis Service objects, such as performing back-ups and processing objects. This Management Studio also provides an Analysis Service Script project in which you develop and save scripts written in Multidimentional Expression (MDX), XML for Analysis (XMLA), and Data Mining Extensions (DMX). The user can also use Analysis Service Scripts projects to perform management tasks or re-create objects, such as database and cubes, on Analysis Service Instances.

• Managing Integration Service Solutions

SSMS enables the user to use the Integration Services service to manage packages and monitor running packages. The user can also use it to organize packages into folers, run it, import and export packages, migrate Data Transformation Services (DTS) packages, and also upgrade Integration Services packages.

• Managing Reporting services Projects

By using the SSMS, it can enable the Reporting Service feature, administer the server and databases, and manage the roles and jobs. The SSMS also enables the user to manage shared schedules by using the Shared Schedules folder, and manage report server databes (ReportServer, ReportServerTempdb). The user can also create a RSExecRole in the Master system database when the user move a report server database to a new or different SQL Server Database Engine (SQL Server Database Engine).

Since we discussed about SSMS, for those who are not familiar with it might wanna ask and do some research more about SQL. Here is some explanations about what is SQL and also the usage of it. SQL stands for Structured Query Language, which is a critical tool for data professionals. The SQL is the most important language for data professionals like data analysis and data sciences.

All data that are being generated every minute, including raw data are stored in databases and professionals using SQL to extract the data for further analysis. SQL is the most common language for extracting and organizing data that is stored in a relational database. A database is a table that consists of rows and columns. SQL in the language of databases, which facilitates retriving specific information from databases that are further used for analysis. When the user did the analysis on another platform like using Python or R, SQL would be needed to extract the data that you need from a company's database.

There are different versions and frameworks for SQL, the most commonly used is MySql. MySql is an open-source solution that helps facilitate SQL's role in managing back-end data for web applications. Companies such as Facebook, Instagram, Whatsapp, and etc. All of these company use SQL for back-end data storage and data processing solutions. When an SQL query is written and run, it is processed by a query optimiser. The query reaches SQL server, where it compiles in three phases; Parsing, Binding, and Optimisation.

• Parsing, A process to check the syntax

• Binding, A process to check the query semantics

• Optimisation, A process to generate the query execution plan

In the third step, all possible permutations and combinations are generated to find the most effective query execution plan in a reasinable time. The shorter the query take, the better it is.

The use of SQL, this is use to data analysis and data science professionals. It is particularly very helpful because it can :

• Execute queries against a database

• Retrive data from a database

• Update records in a database

• Insert records into a database

• Delete records from a database

• Create new databases, or new tables in a database

• Create stored procedures and views in a database

• Set permissions on tables, procedures, and views

In using SQL, there are some commands that the user might need to learn and identify first. These commands are important to help the user in using the SQL, and here are some of the commands usually used in SQL:

• CREATE: Creates new table, a view of table, or another object in the database

• ALTER: Modifies an existing database object, such as table

• DROP: Deletes an entire table, a view of a table or other objects in the database

• SELECT: Retrives certain records from one or more table

• INSERT: Creates a record

• UPDATE: Modifies a record

• DELETE: Deletes a record

• GRANT: Gives a privilage to users

• REVOKE: Takes back privileges granted from users

• AND: Combines two conditions, which must be true for the row to be included in the result test

• AS: Allows the user to rename a column or table using an alias

• AVG(): Aggregate function that returns the average value for a numeric column

• BETWEEN: Used to filter the result set within a certain range, the values can be numbers, text, or dates

• CASE: Used to create different outpurs

• COUNT(): Takes the name of a column as an argument and counts the number of rows where the column is not null

• CREATE TABLE: Creates new table in database, allows the user to specify the name of the table and the name of each column in the table

• GROUP BY: A Clause in SQL that is used only with aggregate functions

• HAVING: Was added to SQL because the 'Where' keywoard could not be used with aggregate functions

• INNER JOIN: Will combine rows from different tables if the join condition is true

• IS NULL/ IS NOT NULL: Are operators used with the 'Where' clause to test for empty values

• LIKE: Is a special operator used with the 'Where' clause for a specific pattern in a column

• LIMIT: Is a Clause that lets the user to specify the maximum number of rows the result set will have

• MAX(): Is a function that takes the name of a column as an argument and returns the largest value in that column

• MIN(): Is a function that takes the name of a column as an argument and returns the smallest value in that column