Business Intelligence(BI) is all about fetching crude data from a data source, converting it into utilizable data, and consuming it for making reports and explanatory graphics for the data analysis. Visually representing the tabular data is known as data visualization. It allows us to visualize the essential information through graphs, charts, maps, KPIs, etc. MSBI(Microsoft Business Intelligence) is a famous suite tool in the Business Intelligence domain. It enables retrieving and storing the data for rapid decisions and smart processing. The MSBI suite contains tools like BIDS(Business Intelligence Development Studio), SSAS, SSRS, SSIS, and Data Warehouse. The demand for SSRS, SSAS, and SSIS professionals is increasing gradually, and many organizations are looking for skilled business intelligence candidates. So, if you want to make a promising career in the Business Intelligence field, join our MSBI training. Ziprecruiter.com shows that an MSBI developer can earn more than $124k per annum.
|In this MSBI Tutorial, I will be discussing the following topics:|
Microsoft Business Intelligence or MSBI in short makes use of Microsoft Excel to perform data analysis. Because of the use of Microsoft Excel as an easy way of data analysis, data collection and eye-catching reports are easy to generate. SQL Server table is used to grab the data using a spreadsheet.
MSBI has three further types:
SSIS is a data integration service that combines data from many sources such as Sybase, Oracle, Text, Excel, and MySQL into a single format, after which it refreshes and cleans the data. The OLTP (Online Transaction Processing) module of MS SQL Server is used to complete this integration process.
SSAS stands for "analyze service," and it analyses the data that has been saved. The OLAP (Online Analytical Processing) component and data mining capabilities are both used by SSAS. To do data analysis and obtain useful information, it creates multi-dimensional structures known as CUBES (multidimensional data sources which have dimensions and facts) and mining models.
SSRS is a reporting service that is now used to display and analyze data in a graphical fashion. SSRS provides reports to analyze data, such as reports, plans, dashboards, scorecards, and Excel.
|If you want to enrich your career and become a professional in MSBI, then enroll in "MSBI Training" - This course will help you to achieve excellence in this domain.|
Following are the features and uses of MSBI:
MSBI is a popular software for smart businesses. It consists of the tools to solve queries of the businesses. It enables users to improve their access to correct and up-to-date information in order to make better business decisions. It also includes a variety of tools for various procedures that are vital in BI solutions. MSBI consists of the following components in its architecture:
Data is the starting point for any transaction or event analysis. When data is appropriately evaluated utilizing various BI approaches, it becomes information.
A database is a structured collection of data that can be retrieved using a variety of tools or queries.
are particularly built software apps that interact with users, other tools, or the database itself based on business needs. A general-purpose database management system is built in such a way that it can create, modify, and administer databases as needed.
This tool is useful for corporate analysis and reporting. It is a central repository for MSBI and is an output of integrated data from numerous sources. A data warehouse may hold both current and historical data, making corporate reporting and data analysis far more straightforward than you might anticipate. By summarising the facts, it assists top management in making speedy decisions.
Extract, transform, and load (ETL) is an acronym for extract, transform, and load. It takes data from a variety of sources in various formats, transforms it into a usable format, and feeds it into a final destination such as a data warehouse or data mart.
This component of the engine is responsible for driving and creating relational databases.
A data mart is a tiny section of a data warehouse that provides summarized information.
|Storing the current data (always a production environment)||Storing historical and current data from multiple locations|
|Perform all DML (create, update, read, delete) operations||Perform only read operation|
|High Availability||Flexible access to data|
|Normalized database||De-normalized with fewer tables because of less performance with a large volume of data.|
|Data will update frequently||Periodically update the Data|
|Power BI is a suite of tools that enables us to convert raw data into visual reports and share them in the cloud.||In MSBI, SSRS integrates programming interfaces and processing components for deploying and testing the reports.|
|It can access the data from both cloud storage and on-premises.||It is on-site software, and it cannot use the data from the cloud storage.|
|Power BI has the best data modeling and visualization tools for high-level visual representation.||It has a drill-down capacity that allows us to focus the classified data in a comprehensive manner.|
|Power BI can handle the data up to 33,000 rows or 10MB. If the data surpasses the limit, we must execute the queries in the system.||MSBI can manage big datasets without emphasizing the data engine.|
|It enables us to create data models, dashboards, and reports that Power Apps and other web browsers can use.||In MSBI, we can use only SSRS for creating visualizations and reports.|
|PowerBI offers AI features that allow even non-technical professionals to create reports by developing queries in a natural language.||MSBI needs previous knowledge of programming and data analysis.|
|DTS (Data Transformation Services)||SSIS (SQL Server Integration Services)|
|Limited error handling||Complex and powerful error handling|
|Message boxes in ActiveX scripts||Message boxes in .Net scripting|
|No deployment wizard||Interactive deployment wizard|
|A limited set of transformation||A good number of transformations|
|No business intelligence functionality||Complete business intelligence transaction|
Errors might arise when a data flow component transforms column data, extracts data from sources, or loads data into destinations. Unexpected data values are a common cause of errors.
Following are the types of errors:
This command applies aggregate functions to Record Sets in order to generate new output records from aggregated values.
Adds metadata to packages and tasks at the package and task level, such as Machine Name, Execution Instance, Package Name, Package ID, and so on.
Changes string data at the SQL Server level, such as changing data from lower to upper case.
Splits available input into multiple output pipelines using Boolean Expressions for each output.
Make a copy of the column in the output so that we can transform it later while maintaining the original for auditing.
Converts column data types from one type to another. Explicit Column Conversion is what it stands for.
This command is used to run data mining queries against analysis services and to manage Predictions Graphs and Controls.
From specified expressions, create a new (computed) column.
This command is used to export a single Image column from a database to a flat-file.
A data purification technique that identifies rows that are probable duplicates.
A fuzzy logic-based pattern matching and ranking algorithm.
This command reads an image-specific column from a database and saves it to a flat-file.
Looks up (or searches) a set of reference objects against a data source. It's only used for exact matches.
This command combines two sorted data sets into a single data flow.
A join junction is used to combine two data sets into a single dataset.
Duplicates the Data Source and sends it to several Destinations.
Saves the result of the data flow/transformation as a variable.
Captures sample data by using a row count of the total rows in the data flow.
Merge numerous data sets into a single dataset with UNION ALL.
Used to turn rows into columns in order to normalize data sources and reduce anomalies.
In the case of creating Data Warehouses, UNPIVOT is used to demoralize the data structure by converting columns to rows.
|Explore - MSBI Career Opportunities|
Following are the languages used in SSAS:
Three types of parameters are used in SSAS:
In SSRS, we have three kinds of users of reporting services:
We have many data sources like Oracle, MySQL, etc. We can connect any of these data sources to Microsoft SQL Server. After connecting the data sources to SQL Server, the data rendering and retrieval process will happen. Data rendering is a process of analyzing and filtering the data for satisfying the requirements. Report processing takes place after data rendering. Report Processing is a process of filtering, modifying, and publishing the available reports. To publish the reports on the website, we use the XML web service interface.
We can explain SSRS working through the following steps:
This term refers to a set of applications and technologies that enable the gathering, storage, manipulation, and reproduction of multidimensional data for the purpose of analysis.
This word refers to a specific type of Cartesian data structure. In this way, MOLAP differs from ROLAP. Joins between tables are already suitable in the former, which improves performance. Joins are computed during the request in the latter. Because it's a shared environment, it's aimed at groups of people. The information is kept in a server-based format. It performs greater in-depth data analysis.
Small OLAP products for multidimensional analysis on a local scale OLAP on the desktop. A tiny multidimensional database can be created (using Personal Express), or a datacube can be extracted (using Business Objects). It is designed for a single, low-end departmental user. On the desktop, data is kept in cubes. It's almost as though you had your own spreadsheet. End users don't have to worry about performance issues with the server because the data is local.
One or more star schemas are kept in relational databases under this name. With data stored in relational databases, this technology allows for multidimensional analysis. Because it handles enormous volumes of data and users, it is ideal for large departments or groups.
Hybridization of OLAP
|Explore MSBI Sample Resumes Download & Edit, Get Noticed by Top Employers!|
To implement MSBI, business experts must first be familiar with MSBI. MSBI tutorial can assist businesses in making appropriate business decisions and preparing their business strategy. In essence, business intelligence is a collection of plans for gathering and analyzing data. The data is typically present in large volumes here, and you can also apply new company concepts.
Anjaneyulu Naini is working as a Content contributor for Mindmajix. He has a great understanding of today’s technology and statistical analysis environment, which includes key aspects such as analysis of variance and software,. He is well aware of various technologies such as Python, Artificial Intelligence, Oracle, Business Intelligence, Altrex etc, Connect with him on LinkedIn and Twitter.