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CoursesData Analytics And Bi Training
Data Analytics Certification Training
Data Analytics And Bi Training
Data Analytics Certification Training

With our Data Analytics Certification Training by Techpratham, you'll learn how to turn raw data into useful information. Find out how to use tools, techniques, and frameworks to make business decisions based on data.

5/5(4,890 Reviews)

Level

Advanced

Duration

8 Weeks

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About Data Analytics Certification Training

This course covers all the basics of data analytics, including how to collect, clean, visualize, and model data to make predictions. You will learn how to use industry tools like Excel, SQL, Python, and Tableau/Power BI by doing them yourself. Find out how to read complicated datasets, make dashboards that matter, and use analytics to solve real-world business problems. After this training, you'll be ready for jobs in business intelligence and data analysis.

Training Plan

01

About trainer

Working professional who is carrying more then 10 years of industry experience.

02

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

03

e-Book

E-book provided by TechPratham. All rights reserved.

04

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

05

Video Recording

Daily Session would be recorded and shared to the candidate.

06

Projects

Live projects will be provided for hands-on practice.

07

Resume Building

Expert-guided resume building with industry-focused content support.

08

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

Data Analytics Certification Training Course Curriculum

Introduction to Data Analytics

Understand the fundamentals of data analytics and its business applications.

Data types
Data lifecycle
Business use cases
Tools & technologies

Data Collection & Data Sources

Recognize how to collect data from various sources, both structured and unstructured.

Primary vs Secondary data
Databases, APIs, spreadsheets, logs
Web scraping basics
Data warehousing concepts

Data Preparation & Cleaning

To ensure accurate analysis, learn how to clean, transform, and preprocess data.

Handling missing values & duplicates
Data transformation & normalization
Outlier detection
Data pipelines (ETL: Extract, Transform, Load)

Exploratory Data Analysis (EDA)

Find trends, identify abnormalities, and provide a statistical and visual summary of datasets.

Descriptive statistics (mean, median, variance, correlation)
Data profiling
Visual exploration with charts & graphs
Tools: Python (Pandas, Matplotlib), Excel

Data Visualization

Develop your ability to convey ideas through captivating and understandable images.

Principles of effective visualization
Dashboards & storytelling with data
Tools: Power BI, Tableau, Excel
Advanced visualizations (heatmaps, treemaps, interactive charts)

Statistical Analysis for Data Analytics

Utilize statistical methods for data analysis and interpretation.

Probability distributions
Hypothesis testing
Regression analysis (linear & logistic)
Correlation & causation

Data Analytics And Bi Training Courses

No related courses found

Additional Program Highlights

Learning Materials
Resume Writing
Interview Preparation
Interview Preparation

Upcoming Batches

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Who Should Take Data Analytics Certification Training

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Job Roles For Data Analytics Certification Training

Key Projects

Data Analytics Certification Training

Google

GoogleSearch Insight Optimizer


Scenario: Analyzed large scale search and ad data to uncover user behavior trends improve campaign targeting accuracy and build dashboards for strategic decisions

Live Work:

  • Built BigQuery data models
  • Designed Looker KPI dashboards
  • Created Python trend analysis
Outcome: Improved ad targeting and ROI growth
Amazon

AmazonRetail Demand Forecast Hub


Scenario: Developed predictive analytics models using sales inventory and customer data to forecast demand reduce stock gaps and support supply chain planning

Live Work:

  • Built demand forecasting model
  • Cleaned data using SQL
  • Automated weekly KPI reports
Outcome: Reduced stock outs and excess cost
Meta

MetaSocial Engagement Metrics Lab


Scenario: Processed social media interaction data to measure engagement optimize content reach and provide insights for data driven marketing strategies

Live Work:

  • Analyzed engagement patterns
  • Built Power BI dashboards
  • Created audience segmentation
Outcome: Increased campaign engagement rate
Microsoft

MicrosoftCloud Usage Intelligence


Scenario: Evaluated cloud platform usage data to track performance trends optimize resource allocation and support enterprise decision making

Live Work:

  • Modeled Azure usage data
  • Designed executive dashboards
  • Automated cost analysis
Outcome: Optimized cloud cost efficiency

Placement Process

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Our Success Mantra

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Commitment

  • Ensuring quality training every day

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  • Meeting learning goals with confidence

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Accomplishment

  • Students achieving industry-ready expertise

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Beyond Courses:

Additional Support We Provide

24/7 Support

LinkedIn Profile

Resume Writing

Alumni Sessions

Interview Preparation

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Industry-Recognized Certification

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