Power BI ilə biznes analitikasıTopics

In the topic, the concept of big data (big data), which is growing rapidly in the modern business environment, its fundamental characteristics and the role it plays in business analytics are studied. students are introduced to the different types of databases and data storage environments that serve as sources for analytical reporting.

The subject studies the essence of data analytics, which is the process of collecting, cleaning, transforming and transforming raw data into useful information for business. students are introduced to the main types of analytics and the importance of a data-driven approach to modern business decision-making.

In the topic, the main decision-making criteria and methodologies used in the process of turning raw data into strategic decisions in business analytics are studied. students are introduced to the principles of defining key performance indicators, comparing target and actual indicators, and defining analytical criteria that accelerate decision making in power BI reports.

The topic explores the concept of business intelligence (bi), its relationship with data analytics, and its role in turning raw data into strategic decisions. students analyze the differences between traditional BI systems, which are highly dependent on it, and modern "self-service bi" (power bi), which allows user-oriented, rapid visualization. also, market-leading analytical tools power bi, tableau and qlikview are compared in terms of functionality, price and ease of use.

The topic explores the interface, main dashboards and ribbon menu of power BI desktop, the main analytical tool of the power BI ecosystem. students experience mechanisms for securely connecting to different data sources (excel, csv, SQL server, web pages, etc.) and importing raw data into a software environment to produce analytical reports.

In the topic, power query editor, an ETL tool used for cleaning, transforming and structuring raw data within power bi, is studied. students master the mechanisms of eliminating type mismatches, deleting unnecessary columns and rows, grouping data, repositioning rows and columns, and joining different tables.

The topic delves into the applied steps panel, which controls the internal sequence of each operation performed during data cleaning in power query editor. students can view the execution history and structure changes of formed steps, add a new transformation step between two existing steps, change the execution order of steps, edit the parameters of an existing step, and analyze the effect of removing any applied step on the dependencies between them.

In the topic, the principles of building relational data models, which are the basis of analytical reports on the power BI platform, are studied. students analyze the types of relationships that exist between tables (1:1, 1:m, m:1, m:m), the concepts of primary and foreign keys that provide unique identification. also, mechanisms for automatic detection of relations, manual creation of new relations, management of active/inactive relations and editing/deletion of relations for model optimization in the power BI environment are practically explored.

In the subject, the language of DAX formulas used for the formation of advanced data analysis, dynamic reporting and special business indicators in the power BI environment is studied. students analyze the importance of DAX in the data model, the language's built-in data types, basic syntax rules, and operator types. also, the steps to create computed columns within the model and their storage properties are practically explored.

The topic studies the categories of DAX functions used to realize dynamic calculation scenarios in the power BI model. students are introduced to date and time functions to perform calendar analysis in reports, text functions to clean and combine text-type data, and logical functions to generate different results based on specific business conditions.

The topic explores complex DAX categories used for aggregation and dynamic data adjustment in power BI reports. students are introduced to mathematical and statistical functions for basic calculation operations, as well as the program's most powerful filter functions to completely change the calculation context in power BI and apply custom filters to reports.

In the topic, power BI desktop's main working environment for designing analytical reports and dashboards is studied together with the report view functional units. students are introduced to the fields panel, where data columns are located, the visualizations panel, where visual types are selected and formatted, the ribbon, which connects the toolbar, different view modes, and the pages tab, where report sheets are controlled.

In the subject, methods of grouping and dividing data into categories (binning) are studied in order to present large volumes of data in a more comprehensible and systematic way in the power BI environment. students learn how to form special groups in text-type columns, and how to create bins to divide data into specific ranges in numeric and date-type columns.

In the subject, the hierarchy concept and its practical application are studied, which provides multi-level analysis of data from general to detailed in the power BI environment. students analyze the date hierarchies automatically generated by the software, as well as methods for creating custom date and geographic/product hierarchies according to business requirements. also, the principles of managing drill-up, drill-down and transition to the next level functions, which provide navigation between levels in visuals, are practically mastered.

In the topic, the main types of graphs used for effectively presenting data visually in the power BI environment and the possibilities of their customization are studied. students are introduced to the slicer visual, which allows report users to dynamically filter data, and master table and matrix structures for cross-analysis of complex data. also, the rules for constructing and formatting maps for geographic data, scatter for correlation analysis, waterfall for financial/branch changes and funnel charts for sales milestone analysis are also analyzed in practice as per project requirements.

In the topic, the power BI service (saas) platform, which provides the management of reports in the cloud environment, and its analytical tools are studied. students get acquainted with the interface of the cloud platform, analyze the "quick insights" function, which automatically derives analytical results from data using artificial intelligence tools. also, the concept of panel, which brings together important visuals from different reports, its creation, the configuration and customization of the question-and-answer widget, which allows asking questions about data using natural language, is mastered.

In the topic, methods of effective use and visual optimization of control panels created in the power BI service environment within the team are studied. students analyze how to securely share developed dashboards with other employees and decision-makers within the organization, and how to present visuals and data boxes in full-screen mode. also, the principles of editing the details of the boxes inside the panel, adding external widgets, and visually expanding the dashboard area to obtain maximum awareness on monitor screens are explored.

The subject studies secure and automated communication mechanisms between the power BI service cloud platform and data sources stored in the local network. students analyze different database connection modes and their performance and memory differences. in the practical part of the topic, the direct integration to the SQL server database stored in the company's local network, the connection of reports in the cloud environment with local data files (excel, csv, etc.) and the construction and configuration of the on-premises data gateway software, which ensures automatic data updating, are studied.

In the topic, it is learned how to set up power BI report server and publish reports here to store reports entirely in the company's internal infrastructure. also, in order to protect data privacy, creation of security roles at the row level through DAX formulas and filtering mechanisms are adopted so that users can see only the data rows according to their authority.

In the topic, mechanisms for connecting r and python languages ​​for advanced data analytics, data cleaning and transformation in the power BI environment are studied. students master running complex ETL processes and preparing raw data for analytics using custom r and python scripts within power bi.

The topic explores advanced analytics and cloud-based data architecture capabilities provided by the power BI platform. students master the mechanisms of creating data flows for cloud service connection, centralized management and reuse of big data. also, the function of automatic detection of abrupt changes and anomalies in visuals that deviate from the normal course is practically analyzed using artificial intelligence tools.

The subject studies the creation of score cards used to monitor strategic business goals and key performance indicators of companies. students master connecting data from different reports to a single control panel, setting target indicators and dynamic monitoring of statuses in real time.

In the topic, the application of the sensitivity labels provided by microsoft purview in the power BI environment is studied for the protection of reports and data sources from outsiders. students analyze how data can be labeled according to privacy levels, encrypted, and how these security rules are preserved even when the report is exported to excel.