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Data Analytics course in Pune


Learn Data Analytics in Pune with Aspire Techsoft – the best data analytics training institute offering expert-led classes, real-time projects, and 100% placement support. Master in-demand skills and launch your career in data analytics today!

4.9 out of 5


Course Duration

4 Months

Mode OF Training

Online / Classroom

100% Placement Assistance

Assured

Best Experienced Faculties

8+ years of Experienced

Course Duration 4 Months

Mode OF Training Online / Classroom

100% Placement Assistance

8+ Years Experienced Faculties

PLACEMENT RECORDS

Watch Live Classes

Data Analytics course in Pune
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Data Analytics Training in Pune

Unveil your future in the field of data-driven decision-making with Aspire Techsoft, the best data analytics training institute in Pune. Our comprehensive data analytics course curriculum is designed to equip aspiring professionals and fresh graduates with the most in-demand analytical skills required in today's data-centric world. At Aspire Techsoft, we provide industry-focused Data Analytics Training in Pune that covers all the key areas of data analytics, including data visualizat ...

Data analytics is a rapidly growing field that combines elements of statistics, computer science, and business. Data analytics is the process of observing, cleansing, transforming, and modeling data with the aim of finding useful information, informing conclusions, and supporting decision-making.

Today, large industrial organizations collect large amounts of data from various sources, and data analytics provides tools and techniques to extract valuable insights from this raw data.

Data Analytics enables businesses to understand past performance by identifying trends, patterns, and anomalies. Predict future outcomes, such as forecasting sales or anticipating market changes. Optimize processes to improve efficiency and reduce costs.

Descriptive analytics focuses on understanding past events ("What happened?"). It delves deeper into the data to identify the root causes behind the trends or events identified in the descriptive phase.

Diagnostic analytics seeks to identify the root causes ("Why did it happen?"). It delves deeper into the data to identify the root causes behind the trends or events identified in the descriptive phase.

Predictive analytics uses data to forecast future possibilities ("What might happen?") It leverages historical data and patterns to anticipate future outcomes.

Prescriptive analytics recommends specific actions to optimize outcomes ("What should we do?"). It identifies specific actions to optimize outcomes or achieve desired goals.

Informed Decision-Making

Competitive Advantage

Improved Operational Efficiency

Enhanced Customer Experience

Innovation and Product Development

Personalized Marketing

Cost Reduction

Strategic Planning

Enhanced Security

Finance and Banking

Healthcare

Retail and E-commerce

Manufacturing

Media and Entertainment

Government and Public Sector

Education

Telecommunications

Transportation and Logistics

Energy and Utilities

Human Resources

foundational knowledge for aspiring data analytics professionals, detailing that while formal education is not strictly required, skills in mathematics and statistics, spreadsheet software like Excel, basic programming with Python or R, database querying with SQL, and data visualization are highly beneficial.

Students and fresh graduates in fields such as engineering, computer science, mathematics, statistics, and economics can pursue a data analytics course.

You can benefit by gaining practical, job-ready data analytics skills and increasing your employability in a variety of industries such as IT, finance, healthcare, and retail.

Working professionals looking to upskill in roles such as software developers, business analysts, IT professionals and testers can also take a Data Analytics course from Aspire Techsoft.

Learning data analytics can help you add analytical skills to your profile to move into more strategic, high-paying roles like data analyst or data scientist.

Non-technical professionals in roles like sales, marketing, HR, finance, and operations professionals and Career switchers from BPO, KPO, support, teaching or any non-IT field they can learn data analytics certification course.

Our Data Analytics Course Curriculum covering various analytical approaches and tools, expert instructors with industry backgrounds, and emphasis on hands-on learning through practical projects and real-world data.

Aspire Techsoft Data Analytics course curriculum also incorporates Real-world case studies from industries like finance, healthcare, retail, and logistics.

Our data analytics training on various Tools & Technologies such as Excel, SQL, Python, R, Power BI, Tableau, and Machine Learning platforms.

Instructor-Led Data Analyst classes in Pune taught by experienced industry professionals with certified data scientists.

The course also focuses on Data Analytics career development, offering 100% placement assistance and providing access to industry-recognized certifications.

Students can find Internship opportunities with partner organizations. The Aspire Techsoft institute organizes Campus drives for Data Analytics course in Pune and job fairs for final assessments.

We provide guest lectures sessions from data analysts at top companies. Professionals receive Mentorship support for career and academic guidance.

Our Data Analytics Certification course emphasizes Hands-on Learning through Capstone projects simulating real-world problems. It includes assignments focused on Data storytelling and visualization. Students have Access to live datasets and cloud-based labs.

Aspire Techsoft offers Career-Oriented Data Analytics Skills with sessions for Resume and LinkedIn profile building.

Support includes Mock interviews and career counseling. Our Data Analyst Certification course also helps with Certification preparation for tools like Google Data Analytics, Microsoft Power BI, and more.

Our Data Analytics Certification course in Pune offers Flexible Learning Modes, available in classroom, hybrid, and fully online formats. Weekend and evening batches are available for working professionals. Students get Lifetime access to Data Analyst course materials and recorded sessions.

Our data analytics course includes Data Ethics and Privacy Modules, covering Training on GDPR, data security, and responsible AI. There is an Emphasis on ethical data sourcing and use.

Aspire Techsoft Data Analytics course involves Module-wise quizzes, assignments, and peer reviews. There is a Final certification exam, and upon completion, students receive an industry Recognized course completion certificate.

Python

SQL

Advance SQL

Tableau Tool

Microsoft Power BI Tool

AI Analytics Platform - Alteryx

Advanced Excel

Descriptive statistics

Data visualisation

Data cleaning

Data Transformation

Data Modelling

Dashboard creation

Programming Languages Python, R, SQL

Spreadsheets Microsoft Excel, Google Sheets

Business Intelligence (BI) Tools Tableau, Microsoft Power BI, QlikView

Statistical Software SPSS, SAS

Big Data Technologies Hadoop, Spark (for large datasets)

Cloud Platforms AWS, Azure, and Google Cloud (for scalable storage and processing)

Data Analyst – Tableau

Buiness Analyst

Business Intelligence Analyst

Data Scientist

Data Analyt - Python

Machine Learning Engineer

Data Engineer

The promising future of data analytics, highlighting its rapid evolution driven by AI and machine learning, which are making analysis more automated and predictive.

The increasing need for real-time processing and edge computing to gain immediate insights, alongside a focus on data democratization to make data accessible to a wider audience.

The text also discusses the importance of robust data management, cloud-native solutions, and crucial attention to data governance and ethics.

The changing role of data analysts towards becoming strategic partners and points to promising job prospects in the field.

Data Collection and Management

Data Cleaning and Preparation

Data Analysis and Interpretation

Reporting and Communication

Collaboration and Business Impact

The robust and growing demand for data analytics professionals, emphasizing those businesses increasingly rely on data-driven decisions.

The key trends shaping the market, including the integration of AI and ML, the rise of real-time and augmented analytics, and the growing importance of data privacy and storytelling.

The demand technical and soft skills required for success in the data analytics field, such as proficiency in SQL, Python, power bi, advanced excel, data visualization tools, critical thinking, and communication.

Data analytics is a rapidly growing and in-demand field, particularly in India, offering competitive salaries. The Data Analyst Salaries are increase significantly with experience, ranging from entry-level to principal roles, and are influenced by factors such as location, industry, specific skills, and company size.

Aspire Techsoft offers Corporate Data Analytics Training in Pune program. We provide a foundational course in data analytics covering key techniques and tools like Power BI, Advanced Excel, Python, R Programming, SQL and Tableau, which is suitable for business analysts and those working with large datasets.

Aspire Techsoft also offers more advanced programs in areas like machine learning and deep learning using frameworks like Scikit-Learn and TensorFlow, along with training in data engineering.

Aspire Techsoft also offers more advanced programs in areas like machine learning and deep learning using frameworks like Scikit-Learn and TensorFlow, along with training in data engineering.

We focus on a customized and flexible approach to data analytics corporate training in Pune, our data analytics corporate training is delivered by experienced trainers and covers a wide range of technologies with a strong track record and high client satisfaction.

Pune is an attractive city for young entrepreneurs, students, and creative minds. The city is described as offering more than just career opportunities; it provides a lifestyle that effectively balances work, play, and culture.

Pune city holds the distinction of being the Cultural city of Maharashtra, with a deep-rooted legacy in arts, education, and tradition.

If you are looking for Data Analytics courses in Pune, specifically focusing on "Data Analytics course near me," and generally asking about them. Aspire Techsoft in Pune has a strong ecosystem of training institute offering Data Analytics programs.

Pune has rapidly developed into one of India’s biggest IT hubs in recent decades. This is driven by a booming technology industry that attracts professionals and innovators from across the country. The presence of global tech giants and a growing number of startups supported by incubators and accelerators highlights its innovative spirit.

Pune is dotted with various places that cater to the younger generation, ranging from exciting hangouts to historical landmarks and scenic getaways.

These include popular spots like FC Road, known for its student-friendly cafes and shops; Koregaon Park, recognized for its cosmopolitan vibe, cafes, and nightlife; natural retreats like Vetal Tekdi for treks; entertainment hubs like Phoenix Marketcity; cultural spots like gardens and museums; and adventure destinations like Sinhagad Fort and weekend getaways like Khadakwasla Dam and Lavasa. The presence of vibrant nightlife spots like High Spirits Café further underscores its youthful appeal.

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Data Analytics Course: What You Will Learn?

Fundamentals of Python - This includes syntax, basic data types (integers, floats, strings, booleans), variables, operators, control flow (if/else, loops), functions, and basic data structures (lists, tuples, dictionaries, sets).

Libraries for Data Manipulation - You will learn to use NumPy for numerical operations and array manipulation, and Pandas for loading, cleaning, manipulation, and analysis using DataFrames.

Data Acquisition - Techniques for reading data from various sources like CSV, Excel, SQL databases, and APIs using Python will be covered.

Basic Scripting for Automation - You will learn to write simple Python scripts to automate repetitive data tasks.

Database Fundamentals - Understanding relational databases, tables, columns, rows, primary keys, and foreign keys.

Basic SQL Commands - Learning SELECT for retrieving data, FROM clauses, WHERE for filtering, ORDER BY for sorting, and LIMIT for restricting results. You will also learn Data Manipulation Language (DML) commands like INSERT, UPDATE, and DELETE.

Aggregate Functions - Using functions such as COUNT (), SUM (), AVG(), MIN (), MAX() to summarize data.

Grouping Data - Applying GROUP BY to perform aggregations on subsets of data.

Advanced SQL - This includes mastering Joins (INNER, LEFT, RIGHT, FULL OUTER) to combine data from multiple tables. You will also learn about Subqueries, Window Functions (e.g., ROW_NUMBER(), RANK(), LEAD(), LAG(), NTILE()), Common Table Expressions (CTEs) using WITH clauses, and Set Operators (UNION, UNION ALL, INTERSECT, EXCEPT).

Database Design Principles - An introduction to normalization and denormalization concepts.

You will master Tableau, described as a powerful and intuitive data visualization tool.

Connecting to various data sources, such as spreadsheets, databases, and cloud platforms.

Creating compelling visualizations, including interactive dashboards, charts, graphs, and maps.

Performing data blending and calculations.

Building interactive dashboards.

Sharing and publishing visualizations.

Learning storytelling with data to present findings effectively.

Connecting and transforming data from diverse sources using Power Query Editor.

Building data models by creating relationships and hierarchies.

Writing DAX (Data Analysis Expressions) for custom calculations.

Designing interactive reports and dashboards.

Utilizing Power BI Service for publishing, sharing, and collaboration.

Implementing row-level security.

Beyond basic functions, this module delves into Excel's advanced capabilities for data analysis.

Master advanced formulas and functions like VLOOKUP, HLOOKUP, INDEX-MATCH, SUMIFS, COUNTIFS, and array formulas.

Perform data validation and conditional formatting.

Create and analyze pivot tables and pivot charts.

Work with Power Query in Excel.

Automate tasks with Macros (VBA basics).

Use scenario analysis and goal seek.

The course introduces Alteryx, described as a powerful and user-friendly platform for advanced analytics, data preparation, and blending.

Getting Started with Alteryx - Understanding the Designer Workspace.

Performing data blending and preparation, including cleaning data and handling missing values.

Applying various data manipulation tools like filtering, sorting, joining, aggregating, and transposing.

Building analytical workflows without writing code.

Integrating with other tools.

An introduction to predictive analytics capabilities within Alteryx.

Measures of Central Tendency - Understanding mean, median, and mode.

Measures of Dispersion - Learning about range, variance, standard deviation, and interquartile range (IQR).

Data Distribution - Understanding histograms, box plots, and density plots.

Skewness and Kurtosis - Interpreting the asymmetry and "tailedness" of distributions.

Percentiles and Quartiles - Understanding the position of values within a dataset.

Principles of Good Visualization - Choosing the right chart type and avoiding misleading visuals.

Tools for Visualization - Hands-on experience with libraries like Matplotlib and Seaborn in Python, or potentially BI tools like Tableau/Power BI.

Chart Types - Creating various charts such as bar charts, line charts, scatter plots, pie charts, histograms, box plots, heatmaps, etc.

Storytelling with Data - Designing compelling dashboards and reports.

Interactive Visualizations - Creating dynamic charts depending on the tools used.

Handling Missing Values - Identifying, understanding, and implementing strategies for imputing or removing missing data.

Dealing with Duplicates - Detecting and removing duplicate rows.

Correcting Data Types - Ensuring columns have the correct data types.

Standardizing Formats - Addressing inconsistencies in data entry.

Outlier Detection and Treatment - Identifying and handling outliers.

Handling Inconsistent Data - Cleaning up irregularities and errors.

Feature Engineering - Creating new features from existing ones.

Binning/Discretization - Grouping continuous data into discrete bins.

Text Processing - Basic techniques for cleaning and preparing text.

Scaling and Normalization - Preparing numerical data for certain algorithms (e.g., Min-Max scaling, Z-score normalization).

Aggregating Data - Summarizing data at different granularities.

Understanding Conceptual and Logical Data Models.

Introduction to Dimensional Modeling (star and snowflake schemas).

Creating Relationships - Establishing primary and foreign key relationships.

Introduction to Data Marts and Data Warehouses.

Preparing Data for Machine Learning Models - Structuring data into features (X) and target (y) variables.

Dashboard Design Principles - Best practices for layout, color, interactivity, and user experience.

Choosing the Right Visualizations - Selecting charts that answer business questions.

Key Performance Indicators (KPIs) - Identifying and visualizing critical metrics.

Interactivity - Adding filters, slicers, and drill-down capabilities.

Storytelling with Dashboards - Arranging visualizations to guide users.

Tools for Dashboarding - Practical application using tools like Tableau, Power BI, or Plotly Dash.

Deployment and Sharing - Publishing and sharing dashboards with stakeholders.

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Data Analytics Course Course Duration

Track Week Days Weekends
Course Duration 2 Months 8 Weekends
Hours 1 Hrs Per Day 3 Hrs per Day
Training Mode Live Web/Classroom Live Web/Classroom

Data Analytics Course Curriculum

Trainer Profile

Sumit
8+ years Exprience :

Sumit has 8+ Years as a Data Analytics Trainer, with a proven track record of successfully training individuals and corporate batches in various data analytics concepts and tools.

Experience in designing, developing, and updating comprehensive data analytics training modules, ensuring alignment with industry trends and employer demands.

Proven ability to provide effective mentorship, guide students in building strong project portfolios, and assist with placement readiness programs, including mock interviews and resume building.

Sumit is committed to creating a dynamic learning environment where students can master essential data analytics tools and techniques. Their technical expertise covers a wide range of crucial areas including Programming Languages (Python, SQL, optionally R), Data Visualization & Business Intelligence Tools (Microsoft Power BI, Tableau, Microsoft Excel), Statistical Analysis & Machine Learning (Descriptive and Inferential Statistics, EDA, Introduction to Machine Learning), and Data Wrangling & Cleaning.

Syllabus of Data Analytics

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Introduction to Excel

• Excel Interface Overview

• Navigating the Ribbon

• Understanding Worksheets and Workbooks

• Creating and Saving Workbooks

• Data Entry and Editing

• Customizing the Quick Access Toolbar

• Excel File Formats


Excel Formula

• Basic Arithmetic Formulas (SUM, SUBTRACT, MULTIPLY, DIVIDE)

• AutoSum Function, Cell References (Relative, Absolute, Mixed)

• Common Statistical Functions (AVERAGE, MEDIAN, MODE)

• Text Formulas (CONCATENATE, LEFT, RIGHT)

• Date Formulas (TODAY, NOW, DATE)

• Logical Formulas (IF, AND, OR)


Formula Based Formatting

• Conditional Formatting Rules

• Highlighting Cells Based on Values

• Data Bars, Color Scales, and Icon Sets

• Custom Conditional Formatting

• Managing Conditional Formatting Rules

• Using Formulas in Conditional Formatting

• Applying Conditional Formatting to Pivot Tables


Conditional Statements & Logical Operators

• IF Statements, Nested IF Statements, AND, OR Operators, NOT Operator

• Combining Multiple Conditions

• Using IF with Text, Numbers, and Dates

• Conditional Formatting with Logical Operators


Text Functions

• CONCATENATE (or CONCAT), LEFT, RIGHT, MID, LEN, and TRIM

• UPPER, LOWER, PROPER

• SUBSTITUTE and REPLACE

• FIND and SEARCH

• TEXT Function for Formatting Numbers and Dates


Date and Time Functions

• TODAY and NOW

• DATE and TIME

• DAY, MONTH, YEAR, HOUR, MINUTE, SECOND

• DATEDIF, NETWORKDAYS, EDATE, and EOMONTH


Excel Tables

• Creating and Formatting Excel Tables

• Table Styles and Options

• Sorting and Filtering Tables

• Adding and Removing Table Rows/Columns

• Structured References

• Table Calculations and Totals

• Converting Table to Range


Basic and Advanced Table Operations

• Creating Dynamic Tables

• Using Table Formulas

• Advanced Filtering Techniques

• Using Slicers with Tables

• Advanced Sorting Techniques

• Working with Subtotals

• Merging and Splitting Tables


Data Pivoting with Different Examples

• Creating Pivot tables, PivotTable Fields and Areas

• Grouping Data in PivotTables

• Pivotable Calculations (Sum, Count, Average)

• Creating Pivot Charts

• Filtering Pivot tables with Slicers and Timelines

• Advanced Pivotable Techniques (Calculated Fields, Custom Calculations)


Cell Reference Functions

• Understanding Cell References

• Using Relative References

• Using Absolute References

• Mixed References

• INDIRECT Function

• OFFSET Function

• Linking Cells Between Sheets and Workbooks


LookUp and VLookUp

• Introduction to LookUp Functions

• VLOOKUP Basics

• HLOOKUP Basics

• Using VLOOKUP with Exact and Approximate Match

• Combining VLOOKUP with Other Functions

• Common VLOOKUP Errors and Fixes

• Alternatives to VLOOKUP (INDEX and MATCH)


Excel Data Visualization

• Creating Basic Charts (Column, Line, Pie)

• Customizing Chart Elements (Titles, Legends, Labels)

• Using Sparklines for Miniature Charts

• Creating Combo Charts

• Using Conditional Formatting for Data Visualization

• Creating Heat Maps

• Using Data Bars and Color Scales


Introduction to Power Query

• What is a Power Query?

• Power Query Interface Overview

• Loading Data into Power Query

• Basic Data Transformation (Filter, Sort, Remove Columns)

• Combining Data from Multiple Sources

• Data Profiling in Power Query

• Saving and Loading Data to Excel


Power Query Editor

• Navigating the Power Query Editor

• Applying Basic Transformations (Replace Values, Remove Duplicates)

• Advanced Transformations (Pivot/Unpivot, Group By)

• Creating Custom Columns

• Merging Queries

• Appending Queries

• Managing Query Steps


Formatting Charts

• Creating Column Charts

• Creating Line Charts

• Creating Pie Charts

• Creating Bar Charts

• Creating Area Charts

• Creating Scatter Plots

• Customizing Chart Types and Style


Creating Reports in Excel with Dataset

• Data Preparation and Cleaning

• Using PivotTables for Reports

• Combining Multiple Data Sources

• Adding Visual Elements (Charts, Sparklines)

• Creating Interactive Dashboards

• Automating Report Updates

• Distributing and Sharing Reports

Introduction to Power BI

• Overview of Power BI and its components

• Power BI service vs. Power BI Desktop

• Benefits of using Power BI for data analytics

• Key features and capabilities of Power BI

• Understanding the Power BI ecosystem

• User interface and navigation

• Basic concepts and terminology in Power BI


Installation of Power BI Desktop

• System requirements for Power BI Desktop

• Step-by-step installation guide

• Initial setup and configuration

• Updating Power BI Desktop

• Troubleshooting common installation issues

• Licensing and subscription options

• Importing sample datasets for practice


Connecting Power BI with Other Sources

• Supported data sources in Power BI

• Connecting to databases, cloud services, and files

• Data import methods and best practices

• Managing data connections

• Data refresh and scheduling

• Handling data privacy and security

• Using Power BI gateways


Basic Visualization in Power BI

• Types of visualizations available in Power BI

• Creating basic charts and graphs

• Customizing visualizations (colors, labels, titles)

• Using slicers and filters

• Creating and managing dashboards

• Adding interactivity to visualizations

• Publishing and sharing reports


Advanced Visualization in Power BI

• Using advanced chart types (waterfall, funnel, gauge)

• Creating and using bookmarks

• Implementing drill-through functionality

• Using custom visuals from the marketplace

• Creating dynamic visualizations with DAX

• Advanced interactivity techniques

• Combining multiple visualizations in a single report


Advanced DAX

• Introduction to DAX: Calculated Columns, Measures, and Tables

• Time Intelligence Functions

• Filtering Functions

• Advanced Calculations and Complex DAX Queries

• Optimizing DAX Queries for Performance

• Practical Applications of DAX in Data Models


Introduction to Power Query

• Overview of Power Query and its interface

• Connecting to various data sources

• Understanding the M language

• Basic data import and transformation

• Using the query editor for data preparation

• Managing and combining queries

• Best practices for efficient data queries

SQL Basics for Data Analysis

• Introduction to SQL

• Setting up the SQL environment

• Basic SQL Commands

• Creating and Deleting Databases and Tables

• Importing and Exporting Data from CSV Files


Fundamentals of SQL Query

• Anatomy of SQL Query

• SQL Data Types and Operators

• Filtering and Sorting Data in SQL

• Aggregate functions in SQL


Dealing With Multiple Tables

• Grouping Data – GROUP BY

• HAVING

• Subqueries

• Joining tables using INNER JOIN, LEFT JOIN, RIGHT JOIN & FULL OUTER JOIN

• Alias in SQL queries

• Working with Multiple Tables Using Subqueries

• Using Set Operators

• Aggregating Data from Multiple Tables using GROUP BY and HAVING.


Advanced SQL Joins

• Advanced Join Techniques

• Joining multiple tables

• Handling duplicate records and eliminating duplicates

• Using UNION and UNION ALL to combine data from multiple tables


Type Casting & Math Functions

• Mathematical Functions

• Type Conversion Functions

• Using CASE Statements to Perform Conditional Operations


DateTime & String Functions

• Working with date/time data in SQL

• Date/time functions

• Formatting date/time data

• String manipulation functions (e.g. UPPER, LOWER, LEFT, RIGHT, etc.)

• Regular expressions in SQL for string operations

• Using CONCAT_WS to concatenate strings with a separator


Window Functions

• Syntax of Windows Function

• Ranking functions (e.g. ROW_NUMBER, RANK, DENSE_RANK, etc.)

• Aggregate functions using windows (e.g. SUM, AVG, MAX, MIN, etc.)

• Partitioning data for window functions

• Understanding the difference between row-based and aggregate-based window functions


Complex queries using CTE & Pivoting

• Common Table Expressions(CTE)

• Recursive CTEs for Hierarchical Data

• Combining CTEs with Window Functions and Subqueries

• Understanding the Performance Implications of CTEs


Database Management & Schema Design

• Understanding The Relational Model and Database Schema Design

• Normalization and Denormalization of Database Tables

• Database Administration Tasks

• Implementing Indexes and Constraints for Data Integrity

• Designing Efficient Database Queries for Performance Optimization

Introduction to Alteryx

• Overview of Alteryx

• Key Features and Benefits

• Use Cases and Applications

• Comparison with Other Data Analytics Tools

• Alteryx Designer Interface

• Licensing and Pricing

• Alteryx Community and Resources


Installation of Alteryx

• System Requirements

• Step-by-Step Installation Guide

• Post-Installation Configuration

• Licensing and Activation

• Troubleshooting Common Installation Issues

• Updating Alteryx

• Uninstalling Alteryx


In/Out Tools

• Input Data Tool

• Output Data Tool

• Directory Tool

• Text Input Tool

• Download Tool

• SharePoint Input Tool

• Blob Input Tool


Preparation Tools

• Data Cleansing Tool

• Filter Tool

• Select Tool

• Sort Tool

• Sample Tool

• Unique Tool

• Generate Rows Tool


Join Tools

• Join Tool

• Union Tool

• Find Replace Tool

• Append Fields Tool

• Make Group Tool

• Fuzzy Match Tool

• Spatial Match Tool


Transform Tools

• Cross Tab Tool

• Transpose Tool

• Formula Tool

• Multi-Field Formula Tool

• Running Total Tool

• Tile Tool

• Imputation Tool


Reporting Tools

• Table Tool

• Charting Tool

• Layout Tool

• Render Tool

• Report Map Tool

• Text Box Tool

• Email Tool


Database Tools

• Connect In-DB Tool

• Data Stream In Tool

• Filter In-DB Tool

• Formula In-DB Tool

• Join In-DB Tool

• Summarize In-DB Tool

• Write Data In-DB Tool


Documentation Tools

• Comment Tool

• Tool Container

• Block Until Done Tool

• Message Tool

• Summarize Tool

• Tool Annotation

• Metadata Output Tool


Full Workflow

• Designing a Workflow

• Best Practices for Workflow Management

• Debugging and Error Handling

• Workflow Automation

• Performance Optimization

• Sharing & Collaboration

• Real-World Workflow Examples

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Mock Interviews

 

Mock interviews by Aspireit give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.

 

In our mock interviews will be conducted by industry best SAP Training experts with an average experience of 10+ years. So you’re sure to improve your chances of getting hired!

SUCCESSFULL PLACED STUDENT'S

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Exam & Certification

When you complete the Data Analytics Course at Aspire Techsoft Pune and complete the hands-on project, you will receive an ISO certificate that you can share with potential employers and your professional network.

Talk about it on Linkedin, Twitter, Facebook, boost your resume or frame it- tell your friend and colleagues about it.

Share your Certification with potential employers to show off your skills and capabilities

Enquire Now Get Certification
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Data Analytics FAQS

Data Analytics is defined as the process of inspecting, cleansing, transforming, and modeling data. The goal of this process is to discover useful information, inform conclusions, and support decision-making.

In the modern world, businesses collect vast amounts of data. Data analytics helps them understand this data, identify trends, predict future outcomes, and optimize their operations. This leads to better business decisions and a competitive advantage.

Studying our Data Analytics course can help you become proficient in data analytics and prepare you for roles such as data analytics, business analytics, and reporting analytics.

Our main objective is to help you become proficient in data analytics tools and methodologies.

Yes, Aspire Techsoft focuses on providing hands-on Data Analyst training through real-time projects, industry-relevant case studies, and practical exercises.

We Aspire Techsoft have experienced industry expert trainers who are eager to share their knowledge. Some reviews mention working professional trainers.

The demand for data analysts is described as very high across various industries, including tech, finance, healthcare, and retail. Common job roles include Data Analyst, Business Intelligence Analyst, Marketing Analyst, Financial Analyst, and Healthcare Analyst, among others.

While some programming knowledge, particularly in Python or R, can be beneficial, many beginner-friendly courses are designed for individuals with little to no prior programming experience. These courses often start with the fundamentals.

A basic understanding of mathematics and statistics is helpful. Some data analyst courses may require a bachelor's degree, but many are open to anyone interested in learning the field.

In Aspire Techsoft we offer Reputable data analytics courses in Pune typically include hands-on projects, case studies, and real-world datasets. This is considered crucial for building a portfolio.

Yes, we provide "100% placement support for data analyst training in Pune" and "placement-oriented Data Analytics classes in Pune”. It includes an internal job portal, mock interviews, and resumes building for you. You will get placement assistance after completing our Data Analytics certification course in Pune.

Yes, a certificate is awarded upon successful completion of the data analyst course at Aspire Techsoft.

Data Analytics focuses on extracting insights from existing data to understand past and present trends. Data Science is a broader field that includes data analytics but also involves more advanced statistical modeling, machine learning, and predictive analytics to build models that can forecast future outcomes.

Certifications can be valuable, particularly if they come from well-recognized institutions or industry leaders (e.g., Google, IBM). They can demonstrate a foundational understanding and boost your resume. However, practical skills and a strong portfolio are often considered more important.

Expect questions on SQL queries, statistical concepts, data cleaning techniques, data visualization best practices, and behavioral questions about problem-solving and communication.

To stay updated, follow industry blogs, attend webinars, read research papers, join online communities, and continuously practice and experiment with new tools and techniques.

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