The Best Advanced Analytics Course in Hyderabad

About This Course

Advanced marketing analytics (AMA) uses data analysis to improve marketing strategies. AMA helps marketers gain insights into their customers’ behaviour, preferences, and other information to create better campaigns.
It’s important to note that AMA isn’t just limited to marketing. The term also applies to any data collection or analysis. For example, it can include customer service, sales, finance, and operations.


We will cover a few critical components of AMA:
• Data – What are your data sources? From which source do you get the data? What type of data do you generate in-house? If not, what tools are available? Which marketing analytics software are you using?
• Process – How often do you collect new data? Do you validate, sort & organize the data you generate? Are all reports created by a single person or team? How much time and do you invest for generating and validating the data?
• Metrics – How much time and money did it take to execute these goals? How well were they achieved? Regarding how they perform against each other, what was most successful? Who performed best?
Our advanced analytics course will introduce you to some critical concepts behind advanced marketing analytics.
Includes defining what advanced marketing analytics is, highlighting its importance, and discussing what types of businesses have used it for success.
You’ll also learn where this data comes from and which industries are more likely to use advanced analytics.


  • Web data analytics and insights
  • Deliver actionable data driven business insights
  • Reports, Segmentation, Qualitative research.
  • Dashboards & different advance
  • Analytics Platforms
  • Data Analysis Overview
  • Preparing Data for Analysis
  • Typical Data Issues
  • Different Tools for Data Analysis 
  • Development of the Analytics field
  • Four different sorts of analytics
  • Diagnostic Analytics
  • Descriptive Analytics
  • Statistical Analysis
  • Human Input in Various 
  • Types of Prescriptive Analytics
  • A Brief Introduction to the CRIP-DM 
    Model for Business Understanding
    Model for Data Understanding
  • Preparation of Data
  • Modeling
  • Evaluation
  • Deploying


  • Determines the center and dispersion of the value using summary statistics.
  • Central Tendencies Measurement: Median, Mode, and Mean
  • Indicators of Variability Standard deviation, variance, interquartile range, and range
  • Frequency table: This displays the frequency at which certain values occur.
  • Charts: A graphic representation of the value distribution.
  • Line, Column
  • Bar Diagram
  • Charting a waterfall
  • A Tree Chart,
  • Box plot
  • Spread Plots
  • Correlation coefficients 
  • Regression analysis

This Course Include

Skills Covered

Digital Analytics

Defining Key Performance Indicator

Lean Six Sigma

Data Analysis

Customer Acqusition

Campaign Management

Conversion Funnel

Customer Retention and Expansion

Batches We Offer For Digital Marketing Courses in Hyderabad


If you are a student and can manage to come on regular basis then Raghu Gaddam recommends to enroll yourself for regular batches. Our schedule for regular batches is from Monday to Friday, five days a week.

Alternate Batches

If you would like to invest your time for practicing at home, then Raghu Gaddam recommends to enroll yourself for alternate batches. Raghu Gaddam conducts alternate batches in which you need to come 3 Days a week on alternate basis.

Weekend Batches

If you are working or can’t manage to have free time on weekdays, then Raghu Gaddam recommends to enrol yourself for our weekend batches, which is only on Saturdays and Sundays.

Sunday Batches

In case if you are having a busy schedule from Monday to Saturday, then Raghu Gaddam recommends to enrol yourself for a Sunday Special Batch, However you need to discuss the timings with our trainers.



Advanced analytics is a data analysis methodology that employs statistical techniques, deep learning, machine learning algorithms, predictive modeling, and other ways to analyze corporate data from many data sources.

Data/text mining, machine learning, pattern matching, forecasting, visualization, sentiment analysis, semantic analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, and neural networks are examples of advanced analytical approaches.

Advanced analytics technologies improve predictive analytics and give insight into change as it happens, enabling firms to be more responsive and improving forecasts and plans.

Businesses rely on three different forms of analytics to help them make decisions: descriptive analytics, which explain what has actually occurred; predictive analytics, which show us what might happen; and prescriptive analytics, which explain what ought to occur going forward.

A Word of Appreciation From Students

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Our Placement Process

Eligibility Criteria

Placement Trainings

Interview Q&A

Resume Preparation

Aptitude Test

Mock Interviews

Scheduling Interviews

Job Placement