Data analytics converts raw data into actionable insights. It includes a range of tools, technologies, and processes used to find trends and solve problems by using data. Data analytics can shape business processes, improve decision-making, and foster business growth. Data analytics helps companies gain more visibility and a deeper understanding of their processes and services. It gives them detailed insights into the customer experience and customer problems. By shifting the paradigm beyond data to connect insights with action, companies can create personalized customer experiences, build related digital products, optimize operations, and increase employee productivity.
We Covered Data analytics Tools in Training :
Tableau
QlikView
Apache Spark
KNIME
RapidMiner
Python
Splunk
predictive analytics
Sisense
Regression analysis
Spotfire
Apache Storm
Roles and Responsibilities of DATA ANALYTICS :
A data analyst is responsible for organizing data related to sales numbers, market research, logistics, linguistics, or other behaviors. They utilize technical expertise to ensure data is accurate and high-quality. Data is then analyzed, designed, and presented in a way that assists individuals, businesses, and organizations make better decisions.
- Using automated tools to extract data from primary and secondary sources
- Removing corrupted data and fixing coding errors and related problems
- Developing and maintaining databases, and data systems – reorganizing data in a readable format
- Performing analysis to assess the quality and meaning of data
- Filter Data by reviewing reports and performance indicators to identify and correct code problems
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets could be helpful for the diagnosis and prediction
- Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.
- Analyzing local, national, and global trends that impact both the organization and the industry
- Preparing reports for the management stating trends, patterns, and predictions using relevant data
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
- Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
Syllabus of DATA ANALYTICS :
Introduction to Statistical Analysis
• Counting, Probability, and Probability Distributions
• Sampling Distributions
• Estimation and Hypothesis Testing
• Scatter Diagram
• Anova and Chisquare
• Imputation Techniques
• Data Cleaning
• Correlation and Regression
Introduction to Data Analytics
• Data Analytics Overview
• Importance of Data Analytics
• Types of Data Analytics
• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics
• Benefits of Data Analytics
• Data Visualization for Decision Making
• Data Types, Measure Of central tendency, Measures of Dispersion
• Graphical Techniques, Skewness & Kurtosis, Box Plot
• Descriptive Stats
• Sampling Funnel, Sampling Variation, Central Limit Theorem, Confidence interval
Excel: Basics to Advanced
• Excel tutorial
• Text to Columns
• Concatenate
• The Concatenate Function
• The Right Function with Concatenation
• Absolute Cell References
• Data Validation
• Time and Date Calculations
• Conditional Formatting
• Exploring Styles and Clearing Formatting
• Using Conditional Formatting to Hide Cells
• Using the IF Function
• Changing the “Value if false” Condition to Text
• Pivot Tables
• Creating a Pivot Table
• Specifying PivotTable Data
• Changing a PivotTables Calculation
• Filtering and Sorting a PivotTable
• Creating a PivotChart
• Grouping Items
• Updating a PivotTable
• Formatting a PivotTable
• Using Slicers
• Charts
• Creating a Simple Chart
• Charting Non-Adjacent Cells
• Creating a Chart Using the Chart Wizard
• Modifying Charts
• Moving an Embedded Chart
• Sizing an Embedded Chart
• Changing the Chart Type
• Chart Types
• Changing the Way Data is Displayed
• Moving the Legend
• Formatting Charts
• Adding Chart Items
• Formatting All Text
• Formatting and Aligning Numbers
• Formatting the Plot Area
• Formatting Data Markers
• Pie Charts
• Creating a Pie Chart
• Moving the Pie Chart to its Own Sheet
• Adding Data Labels
• Exploding a Slice of a Pie Chart
• Data Analysis − Overview
• types of Data Analysis
• Data Analysis Process
• Working with Range Names
• Copying Name using Formula Autocomplete
• Range Name Syntax Rules
• Creating Range Names
• Creating Names for Constants
• Managing Names
• Scope of a Name
• Editing Names
• Applying Names
• Using Names in a Formula
• Viewing Names in a Workbook
• Copying Formulas with Names
• Difference between Tables and Ranges
• Create Table
• Table Name
• Managing Names in a Table
• Table Headers replacing Column Letters
• Propagation of a Formula in a Table
• Resize Table
• Remove Duplicates
• Convert to Range
• Table Style Options
• Table Styles
• Cleaning Data with Text Functions
• Removing Unwanted Characters from Text
• Extracting Data Values from Text
• Formatting Data with Text Functions
• Date Formats
• Conditional Formatting
• Sorting
• Filtering
• Lookup Functions
• Pivoting
SQL
• Introduction to Oracle Database
• Retrieve Data using the SQL SELECT Statement
• Learn to Restrict and Sort Data
• Usage of Single-Row Functions to Customize Output
• Invoke Conversion Functions and Conditional Expressions
• Aggregate Data Using the Group Functions
• Display Data from Multiple Tables Using Joins
• Use Sub-Queries to Solve Queries
• The SET Operators
• Data Manipulation Statements
• Use of DDL Statements to Create and Manage Tables
• Other Schema Objects
• Control User Access
• Management of Schema Objects
• Manage Objects with Data Dictionary Views
• Manipulate Large Data Sets
• Data Management in Different Time Zones
• Retrieve Data Using Sub-queries
• Regular Expression Support
Tableau
Module 1: Tableau Course Material
• Start Page
• Show Me
• Connecting to Excel Files
• Connecting to Text Files
• Connect to Microsoft SQL Server
• Connecting to Microsoft Analysis Services
• Creating and Removing Hierarchies
• Bins
• Joining Tables
• Data Blending
Module 2: Learn Tableau Basic Reports
• Parameters
• Grouping Example 1
• Grouping Example 2
• Edit Groups
• Set
• Combined Sets
• Creating a First Report
• Data Labels
• Create Folders
• Sorting Data
• Add Totals, Sub Totals and Grand Totals to Report
Module 3: Learn Tableau Charts
• Area Chart
• Bar Chart
• Box Plot
• Bubble Chart
• Bump Chart
• Bullet Graph
• Circle Views
• Dual Combination Chart
• Dual Lines Chart
• Funnel Chart
• Traditional Funnel Charts
• Gantt Chart
• Grouped Bar or Side by Side Bars Chart
• Heatmap
• Highlight Table
• Histogram
• Cumulative Histogram
• Line Chart
• Lollipop Chart
• Pareto Chart
• Pie Chart
• Scatter Plot
• Stacked Bar Chart
• Text Label
• Tree Map
• Word Cloud
• Waterfall Chart
Module 4: Learn Tableau Advanced Reports
• Dual Axis Reports
• Blended Axis
• Individual Axis
• Add Reference Lines
• Reference Bands
• Reference Distributions
• Basic Maps
• Symbol Map
• Use Google Maps
• Mapbox Maps as a Background Map
• WMS Server Map as a Background Map
Module 5: Learn Tableau Calculations & Filters
• Calculated Fields
• Basic Approach to Calculate Rank
• Advanced Approach to Calculate Ra
• Calculating Running Total
• Filters Introduction
• Quick Filters
• Filters on Dimensions
• Conditional Filters
• Top and Bottom Filters
• Filters on Measures
• Context Filters
• Slicing Fliters
• Data Source Filters
• Extract Filters
Module 6: Learn Tableau Dashboards
• Create a Dashboard
• Format Dashboard Layou
• Create a Device Preview of a Dashboard
• Create Filters on Dashboard
• Dashboard Objects
• Create a Story
Module 7: Server
• Tableau online.
• Overview of Tableau Server.
• Publishing Tableau objects and scheduling/subscription.
Power BI
Module 1: Introduction to Power BI
• Get Started with Power BI
• Overview: Power BI concepts
• Sign up for Power BI
• Overview: Power BI data sources
• Connect to a SaaS solution
• Upload a local CSV file
• Connect to Excel data that can be refreshed
• Connect to a sample
• Create a Report with Visualizations
• Explore the Power BI portal
Module 2: Viz and Tiles
• Overview: Visualizations
• Using visualizations
• Create a new report
• Create and arrange visualizations
• Format a visualization
• Create chart visualizations
• Use text, map, and gauge visualizations and save a report
• Use a slicer to filter visualizations
• Sort, copy, and paste visualizations
• Download and use a custom visual from the gallery
Module 3: Reports and Dashboards
• Modify and Print a Report
• Rename and delete report pages
• Add a filter to a page or report
• Set visualization interactions
• Print a report page
• Send a report to PowerPoint
• Create a Dashboard
• Create and manage dashboards
• Pin a report tile to a dashboard
• Pin a live report page to a dashboard
• Pin a tile from another dashboard
• Pin an Excel element to a dashboard
• Manage pinned elements in Excel
• Add a tile to a dashboard
• Build a dashboard with Quick Insights
• Set a Featured (default) dashboard
• Ask Questions about Your Data
• Ask a question with Power BI Q&A
• Tweak your dataset for Q&A
• Enable Cortana for Power BI
Module 4: Publishing Workbooks and Workspace
• Share Data with Colleagues and Others
• Publish a report to the web
• Manage published reports
• Share a dashboard
• Create an app workspace and add users
• Use an app workspace
• Publish an app
• Create a QR code to share a tile
• Embed a report in SharePoint Online
Module 5: Other Power BI Components and Table Relationship
• Use Power BI Mobile Apps
• Get Power BI for mobile
• View reports and dashboards in the iPad app
• Use workspaces in the mobile app
• Sharing from Power BI Mobile
• Use Power BI Desktop
• Install and launch Power BI Desktop
• Get data
• Reduce data
• Transform data
• Relate tables
• Get Power BI Desktop data with the Power BI service
• Export a report from Power BI service to Desktop
Module 6: DAX functions
• New Dax functions
• Date and time functions
• Time intelligence functions
• Filter functions
• Information functions
• Logical functions
• Math & trig functions
• Parent and child functions
• Text functions
Python Basics
• The print statement
• Comments
• Python Data Structures & Data Types
• String Operations in Python
• Simple Input & Output
• Simple Output Formatting
• Deep copy
• Shallow copy
• Operators in python
GOOD OPPORTUNITY FOR FRESHERS
Any Trained Candidates will have only Subject Knowledge, but they will not have real time Exposure….. By Doing this Candidate will get Full Project Exposure and will be able to show Exposure equivalent to real time, which companies r expecting from Fresh Candidates, that will help them to get job Easily……
