Data Analysis Online Course | Data Analytics Training in Hyderabad

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Data Modeling in Power BI
91-9989971070
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Data analytics modeling with Power BI involves
using Microsoft Power BI, a powerful business
intelligence tool, to transform and analyze data
to gain insights, make data-driven decisions, and
create visually appealing reports and dashboards.
Power BI allows you to connect to various data
sources, clean and transform data, build data
models, and create interactive data
visualizations.
Here's a step-by-step guide on how to perform
data analytics modeling with Power BI
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1. Data Import - Launch Power BI Desktop. -
Click on "Get Data" to connect to your data
source. - Power BI supports various sources,
including databases, spreadsheets, web services,
and more. - Import the data into Power BI. You
can preview and select the data tables you
need.  2. Data Transformation - Use Power Query
Editor to clean and transform your data. - This
involves tasks like removing duplicates,
filtering, merging tables, and renaming columns.
- Apply data cleaning operations to ensure data
quality.
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3. Data Modeling - After transforming the data,
you can create relationships between tables if
necessary. - Power BI's data model helps in
establishing these relationships. - Define
measures, calculated columns, and calculated
tables using Data Analysis Expressions (DAX). -
DAX is a formula language used for creating
custom calculations.  4. Data Visualization -
Design interactive reports and dashboards by
adding visuals like charts, graphs, tables, and
maps. - Customize the visuals' appearance,
including colors, fonts, and titles.
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- Use the "Fields" pane to drag and drop fields
onto the canvas to create visuals.  5.
Interactive Elements - Enhance your report's
interactivity with slicers, filters, and
drill-through options. - Users can filter and
explore the data themselves.  6. Publish and
Share - Save your Power BI report (.pbix) and
publish it to the Power BI service or Power BI
Report Server for sharing and collaboration. -
Share your reports with others, grant
permissions, and set up data refresh schedules.
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7. Automation and Alerts - Use Power BI's data
refresh capabilities to keep your reports up to
date automatically. - Create data alerts to
receive notifications when specific conditions or
thresholds are met. 8. Advanced Analytics -
Incorporate advanced analytics into your reports
using built-in AI capabilities or by integrating
with Azure Machine Learning. 9. Security and
Governance - Implement data security and
governance practices to ensure that sensitive
data is protected and compliance requirements are
met.
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10. Continuous Improvement - Monitor the
performance of your reports and dashboards,
gather feedback from users, and make improvements
as needed. Power BI provides various features and
capabilities for data analytics modeling, making
it a versatile tool for data professionals,
analysts, and decision-makers. It allows you to
transform raw data into meaningful insights and
share them with stakeholders in an interactive
and visually appealing manner.
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CONTACT
For More Information About
Data Analytics Online Training
Address- Flat no 205, 2nd Floor,
Nilagiri Block, Aditya Enclave,
Ameerpet, Hyderabad-16
Ph No 91-9989971070 Visit
www.visualpath.in E-Mail
online_at_visualpath.in
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