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Power BI: An Introduction to Microsoft's Business Intelligence Tool

In today's data-driven world, business intelligence (BI) is becoming increasingly important for companies of all sizes. By using data analytics tools, organizations can gain valuable insights that can help them make informed decisions and improve their bottom line. 

Power BI is a cloud-based data visualization and business intelligence platform that allows users to connect to and analyze a wide range of data sources, including Excel spreadsheets, databases, and cloud-based sources like Azure and Salesforce. With Power BI, users can create interactive reports, dashboards, and visualizations that can be shared across their organization, making it easy for everyone to stay on top of key performance indicators (KPIs) and business metrics.

Getting Started with Power BI

To get started with Power BI, you will need to create an account on the Power BI website. Once you have an account, you can download the Power BI Desktop application, which is a Windows application that allows you to create reports and visualizations offline.

After downloading the desktop application, you can connect to your data sources and start creating visualizations. Power BI supports a wide range of data sources, including Excel spreadsheets, databases like SQL Server, Oracle, and MySQL, as well as cloud-based sources like Azure, Salesforce, and Google Analytics.

Creating Reports and Visualizations

Once you have connected to your data source, you can start creating visualizations using the drag-and-drop interface in Power BI. You can choose from a wide range of visualization types, including charts, tables, maps, and gauges. You can also add filters and slicers to your visualizations, which allow you to interactively filter your data based on different criteria.

In addition to creating individual visualizations, you can also create dashboards, which are collections of visualizations that provide an overview of key metrics and KPIs. Dashboards can be shared with other users in your organization, making it easy to stay on top of important metrics and trends.

Power BI also includes a feature called "Power Query," which allows you to transform and clean your data before creating visualizations. With Power Query, you can merge, split, and transform your data in a variety of ways, making it easier to work with and analyze.

Sharing and Collaboration

One of the key features of Power BI is its collaboration and sharing capabilities. With Power BI, you can share your reports and visualizations with other users in your organization, either by publishing them to the web or by sharing them directly within the Power BI service.

You can also set up security and access controls to ensure that only authorized users have access to your data and reports. This allows you to collaborate with other users while still maintaining control over your data and ensuring that it is kept secure.

Conclusion

Power BI is a powerful and versatile business intelligence tool that can help organizations of all sizes gain valuable insights from their data. With its intuitive drag-and-drop interface, wide range of visualization types, and powerful data transformation capabilities, Power BI is an excellent choice for anyone looking to create interactive reports and dashboards.

Whether you are a small business owner looking to stay on top of your KPIs or a large organization looking to gain insights from complex data sources, Power BI has the tools you need to succeed. So why not give it a try today and see how it can help you unlock the full potential of your data?

SQL Training in Hyderabad

what is an SQL server?

SQL Server is a comprehensive, integrated, and secure data platform that associations of all sizes use. As a relational database operation system, it's designed to store and manage colorful data and give users with the ability to query, search, and analyze that data. also, SQL Server provides data encryption, auditing, and backup and restore capabilities for increased security. With its built-in analytics, SQL Server helps associations gain insight into their data and empower them to make data-driven opinions that ameliorate their overall business performance.

Analytics benchmark covered topics
1. DBMS, RDBMS
. SQL, MySQL, SQL, and differences
. Data Types
4. sublanguages
5. operators
6. variable
7. control statements
8. cursors
9. stored procedures, functions
. triggers
11. schemas
12. special clauses
13. connections
14. OLTP
15. Tcl commands
16. subqueries
17. joins
18. views
19. constraints
20. DCL commands
21. special clauses
22. ranking functions
Uses of SQL server
SQL is an essential tool for business holders and professionals, as it can be used to manage complex data. It has simple-to-use visual interface tools, which makes the design and data manipulation process easy. also, it's a cost-effective tool that can be used to store large quantities of data. also, SQL Server provides dependable scalability, making it an ideal result for businesses with large quantities of data.
SQL Server is a popular database operation system that's used to store and recoup data. It's used for a variety of tasks, from managing large quantities of data to create complex operations and websites. SQL garçon also provides a simple interface that makes it easy for inventors to work with the data. also, SQL is largely secure and provides dependable scalability, making them suitable for large-scale businesses and enterprises.
SQL Server job names
SQL jobs can be extremely complex; similarly, it's important for businesses to insure that their server jobs are configured duly. A well-organized job name can help with the clarity and association of the system. For illustration, if an association has a job that's responsible for backing up data, the job should have a name that reflects this purpose. also, job names should contain metadata, similar as the date or time the job was created, in order to insure an accurate inspection trail.
Limitations of Microsoft SQL Server Express
1. Only one processor is used, but up to 4 processor cores.
2. Maximum used RAM
3. A database may have a maximum size of 10 GB.
4. The "SQL Server Agent" service, which controls automatic data backup, for example, is not included.

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                    ADF  TRAINING IN HYDERABAD

                          

ANALYTICS BENCHMARK gratefully says to start ADF Training course with real-time examples and real-life scenarios this course change your life and make you a better analyst in every one session has provable examples, ANALYTICS BENCHMARK there so, many students got the job in MNC companies in ADF means Azure Data Factory, a powerful, scalable, and flexible data integration platform that makes it easy to build, manage, and scale data pipelines. Data is the new currency, and data is the new oil, powering the next generation of digital experiences. Companies must not only harvest data but also turn it into actionable information to improve decision-making and drive business value     

Introduction To Azure data engineer

o Importance of ETL 

o What is ADF 

o Why ADF 

o Advantages compared to traditional ETL tools 

o Different Modern Data warehouse systems in Market 

Introduction to the Azure Data Engineering Products 

Roles and Responsibilities of Azure Data Factory and Data Engineer 

o Different types of data 

o Difference between ADF version1 and version2 o Building Blocks of ADF 

▪ Pipelines 

▪ Activities 

▪ Datasets 

▪ Linked Services 

▪ Integration Runtimes 

Azure Storage Introduction 

 Blob Storage ,Data Lake Storage 

Differences between Data Lake Gen1 and Gen2 o Storage Redundancy options  

 

o Difference between blob storage and data lake gen2 o File Shares 

o Queues 

o Table Storage 

o Load the data from Azure blob storage to Power BI o Load the data from Azure Data Lake to Power BI o Different Tiers in Azure Storage explanation

o Storage Life Cycle Management 

o RBAC (Role-Based Access Control) 

o ACL(Access Control Lists) 

o Shared Access Signatures 

o Access Keys 

Azure Data Factory Practicals 

Copy Activity,and it types 

 

Scenario1 

o Copy the file from one container to another container from the same storage account 

o Copy the file from one storage account container to another storage account container 

Scenario2 

o How to copy the data from Azure SQL to Azure Data Lake Gen2 o How to load the data into Azure SQL Table from Azure Data Lake Gen2 o How to delete the files on a successful copy of entire folder contents 

Scenario3 

o How to copy the files with some pattern to another container 

o How to Get the File Size and delete the files with a size greater than 4MB  

Scenario4 

o Conditional Split with if the condition 

Scenario5 

o Send an email on Pipeline Failure 

Scenario6 

o Migrate all tables of the database into a data lake with a single pipeline 

Parameters 

Scenario7 

o How to apply more than one conditional split in ADF Activities 

Scenario8 

o How to run the pipeline until the file arrives in the Data lake Container

Scenario9 

o How to load the filtered data to the azure SQL table/Synapse table 

o Perform Transformation using script activity 

Data Flows Introduction 

 o Difference between source, sink of “Copy Data” activity And the source, sink of “Mapping Data Flows”. 

Dataflow Scenario1 

o Source as (data lake) Sink as (SQL table) --> by using dataflow source and sink transformation 

Extract data from RDBMS to Data lake --> Apply Filter 

o Filter Transformation (Source --> Filter --> Sink) Execute with Dataflow Activity 

Data Flow Scenario on Select Transformation 

o Select Transformation

● Source --> Select --> Sink (Execute with Mapping Dataflow) 

Derived Column use case 

o Derived column Transformation

Union Transformation use cases 

o Combining one or more datasets with the same schema and writing output to a single file 

o Combining one or more datasets with different schema and writing output to a single file

o Select with union 

Branching Transformation and its use cases 

Exists Transformation 

o Exists transformation and its use cases 

o Exists with Custom Expression 

Lookup transformation and its use cases and types

Conditional split transformation and its use cases 

o Distribute data into multiple datasets based on given conditions o Split datasets  

Join Transformation and its use cases 

Aggregate Transformation and its use cases

Pivot Transformation 

Unpivot Transformation 

Aggregation 

Stringify Transformation 

Parse Transformation 

Flatten Transformation 

Implementation of Incremental data loading using ADF Activities Implementation of SCD (Slowly Changing Dimensions) 

Data Loading to Synapse from Azure Data Lake 

1. Today we are excited to announce that the data factory is now available in Azure.

2.  This new data platform allows you to build, manage, and analyze data in Azure

3. Azure  building a secure data factory for our customers to store, manage, and analyze their data 

4. platform is built on the Microsoft Azure data factory which makes it easy to store, manage, and analyze all of your data in one place

5.azure data is  secure and reliable, making it an ideal environment for building and deploying real-time applications.

ANALYTICS BENCHMARK  presented the Azure Data Factory, a defacto solution for orchestrating data movements. We walked through a basic introduction. We described how to use different connectors and data sources and how to use DirectQuery. Finally, we looked at how to use DirectQuery with the Azure Resource Manager  in these adf training in hyderabad these course provide effortable and  (ARMs).               "THANKING YOU"

  

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  mail;mahesh.abtrainings@gmai.com

sql trainining in hyderabad

analytics benchmark offered SQL training in hyderabad programs that are designed to help students develop advanced SQL skills and build a foundation for further study in this field. The training programs cover a wide range of topics, including P-SQL, T-SQL, advanced SQL, and database security, and this SQL course is designed for beginners and will also be beneficial for those with database design experiences such as those who have worked with power bi, azure data factory and table blue

analytics benchmark provides great course content, useful, easily understandable for students, and also covered all the topics with examples and real-time scenarios

analytics benchmark covered in sql modules

 1.introduction,installation 

 2.different types of sub-languages

 3.operators in sql

 4.types of operators

 5.functions and its explanation

 6.types of functions

 7.schema,types,and uses

 8.top functions

 9.what is constrains

 10. types of constrains,explain

 11.joins,and rules of joins

 12.types of joins

 13.views

 14.advantages of views

 15.types,properties of views

 16.indexes

 17.types of indexes

 18.sub queries 

 19.single row and multi row subquarie

 20.Tcl commands

 21.types of commands 

 22.P-SQL

 23.T-SQL

          

 These topics are covered by analytics benchmark in 45 days course program with less cost it is used fully by each student

SQL, which stands for Structured Query Language, is a programming language used to access and manipulate data in a database, and SQL to store and retrieve data in a database. Learn the basics of SQL, such as simple commands and functions, and how to use them to store and retrieve data in a database. 

  It allows you to create complex queries, and tables that can be run against the database to extract information or change the data in the database. The advantage of using SQL instead of a programming language such as Java or Python is that it is much faster and easier to use and easily understood By nonit background students. This comes at the expense of being able to access the full power of the programming language, but it is still a very powerful language.

  

  The  SQL course is structured in a manner that helps you learn in a step-by-step manner which is great for freshers who are just getting started with SQL.  analytics benchmark trainers use real-world scenarios and examples to help you understand the material, Video, and practice exercises are designed to help you improve your skills. You'll learn everything you need to know to be able to perform basic SQL queries and create tables and we'll go over some of the more advanced uses of SQL, like using- SQL, and P-SQL to build advanced web applications and small coding techniques This  SQL training course in Hyderabad has already helped our students land jobs in big MNC companies like Facebook, Amazon, Netflix and google                "THANKING YOU"

  

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  ANALYTICS BENCHMARK

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  Ph;7799771214 https://abtrainings.com/sql-server-course-training-in-hyderabad/

  mail;mahesh.abtrainings@gmail.com