Greens Technologies in Tambaram is known for offering quality training programs in various IT domains, including data analytics. Here are some aspects that might make Greens Technologies a good choice for data analytics training.
What is Data Analytics?
Data Analytics is the process of examining, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. It involves using various techniques and tools to analyze data and uncover patterns, trends, and relationships. Here are the key components and steps involved in data analytics:
- Data Collection: Gathering data from various sources, such as databases, sensors, logs, and online repositories.
- Data Cleaning: Identifying and correcting errors or inconsistencies in the data to ensure its accuracy and completeness.
- Data Transformation: Converting data into a suitable format for analysis. This may include normalization, aggregation, and other preprocessing steps.
- Data Exploration: Using statistical and visualization techniques to understand the data’s structure, distribution, and key characteristics.
- Data Modeling: Applying mathematical models, algorithms, and machine learning techniques to analyze the data and make predictions or identify patterns.
- Data Interpretation: Translating the results of the analysis into actionable insights, which can inform business decisions or scientific research.
- Data Presentation: Communicating the findings through reports, dashboards, and visualizations to stakeholders in a clear and understandable manner.
Types of Data Analytics:
- Descriptive Analytics: Summarizes past data to understand what has happened. Example: Monthly sales reports.
- Diagnostic Analytics: Investigates the reasons behind past outcomes. Example: Analyzing customer complaints to find the root cause of issues.
- Predictive Analytics: Uses historical data and statistical models to forecast future events. Example: Predicting future sales based on past trends.
- Prescriptive Analytics: Suggests actions to achieve desired outcomes. Example: Recommending inventory levels to minimize stockouts.
Applications of Data Analytics:
- Business: Market analysis, customer segmentation, and financial forecasting.
- Healthcare: Patient diagnosis, treatment optimization, and health trend analysis.
- Sports: Performance analysis, strategy development, and injury prevention.
- Government: Policy making, resource allocation, and fraud detection.
- Science and Research: Hypothesis testing, experimental analysis, and data-driven discoveries.
Data analytics is a multidisciplinary field that combines elements of statistics, computer science, and domain expertise to turn raw data into valuable insights.
Our Services
Descriptive Analytics – Understand what has happened in your business with detailed reports and visualizations. Track performance metrics, identify trends, and make data-driven decisions.
Diagnostic Analytics – Dive deep into your data to uncover the reasons behind trends and outcomes. Identify root causes, pinpoint issues, and take corrective actions with confidence.
Predictive Analytics – Stay ahead of the curve by forecasting future trends and behaviors. Leverage advanced statistical models and machine learning to predict sales, customer behavior, and more.
Prescriptive Analytics – Make informed decisions with recommendations based on your data. Optimize your operations, improve resource allocation, and achieve your business goals efficiently.
Industries We Serve
Business
Boost your market analysis, customer segmentation, and financial forecasting. Make strategic decisions with confidence.
Healthcare
Enhance patient outcomes, optimize treatment plans, and analyze health trends. Turn data into better healthcare solutions.
Retail
Improve inventory management, personalize customer experiences, and increase sales. Use data to drive your retail success.
Finance
Identify market trends, manage risks, and optimize investments. Leverage data for better financial planning.
Manufacturing
Optimize production processes, improve quality control, and reduce downtime. Utilize data for smarter manufacturing.
How It Works
- Consultation: We start with a detailed discussion to understand your needs and objectives.
- Data Collection: We gather and clean your data to ensure accuracy and completeness.
- Analysis: Our experts apply advanced techniques to analyze your data and uncover insights.
- Reporting: We present our findings in clear, actionable reports and visualizations.
- Implementation: We help you implement data-driven strategies to achieve your goals.
Why should I choose data analytics?
Choosing data analytics as a career or field of study offers numerous benefits and opportunities, making it a compelling choice for many individuals. Here are several reasons why you should consider pursuing data analytics:
High Demand and Job Opportunities
- Growing Field: Data analytics is a rapidly growing field with increasing demand across various industries, including finance, healthcare, retail, and technology.
- Job Security: As organizations continue to collect vast amounts of data, the need for skilled data analysts to interpret and leverage this data is rising, leading to strong job security.
- Diverse Roles: Data analytics offers a wide range of roles such as data analyst, data scientist, business analyst, and data engineer, allowing for diverse career paths.
Competitive Salaries
- Attractive Compensation: Data analysts often earn competitive salaries, with potential for significant growth as you gain experience and expertise.
- Performance Bonuses: Many organizations offer performance-based bonuses and incentives for data professionals who can drive business results.
Impactful Work
- Informed Decision-Making: Data analysts play a crucial role in helping organizations make data-driven decisions, leading to better outcomes and improved efficiency.
- Problem Solving: The field involves solving complex problems, providing innovative solutions, and contributing to strategic planning.
Skill Development
- Technical Skills: Gain proficiency in various tools and technologies such as SQL, Python, R, Tableau, Power BI, and machine learning algorithms.
- Analytical Thinking: Develop strong analytical and critical thinking skills, which are valuable in many professional and personal contexts.
- Continuous Learning: The field of data analytics is constantly evolving, offering continuous learning opportunities and keeping your skills up-to-date.
Versatility and Applicability
- Industry Versatility: Data analytics skills are applicable across a wide range of industries, providing flexibility to work in sectors that interest you.
- Business Versatility: The skills you acquire in data analytics can be applied to various business functions, including marketing, operations, finance, and product development.
Collaborative Environment
- Team Collaboration: Work closely with different teams, including marketing, finance, and IT, fostering a collaborative and interdisciplinary work environment.
- Communication Skills: Enhance your ability to communicate complex data insights to non-technical stakeholders, improving your overall communication skills.
Future-Proof Career
- Emerging Technologies: Stay at the forefront of technological advancements such as artificial intelligence, machine learning, and big data, ensuring your career remains relevant.
- Adaptability: The skills and knowledge gained in data analytics make you adaptable to various roles and industries, providing career longevity.
Personal Satisfaction
- Intellectual Challenge: Enjoy the intellectual challenge of working with data, uncovering patterns, and deriving meaningful insights.
- Achievement: Experience a sense of accomplishment from turning raw data into actionable insights that drive real business value.
Topics Covered:
Course Name: Power BI
- Tools: Microsoft Power BI
Topics
- M Query
- Power Query Editor
- Data types
- Column Tracking
- Split columns
- Choose column
- Keep / Remove Rows
- Append Queries
- Duplicates Queries
- Creating Dim Table
- Join Kind
- Merge Queries
- Join
- Extract
- Format
- Functions
- Course Name : Power BI
- Tools : Microsoft Power BI
- TABLEAU – POWER BI SYLLABUS
- DATA ANALYTICS
- TABLEAU-POWER BI-SQL-PYTHON
- Data Modeling
- DAX Functions
- Data Types
- Basic Functions
- Date Function
- Aggregation Functions
- Logical Function
- Filter Function
- Time Intelligence Function
- Information Function
- POWER BI VISUALAZATION:
- Dashboards
- Formatting
- POWER BI SERVICE
Course Name: Tableau
- Tools: Tableau
Topics
- Tableau interface demo
- Tableau Products
- Tableau Desktop
- Data types in tableau
- Types of Connection
- Dimension and measures
- Tableau file extension
- Set, Parameter, Group
- Bin, Hierarchy, Combine
- Sorting, Types of Axis, Maps
- Filters
- Quick Table Calculation
- Analytics Functions
- Logical Functions
- String Functions
- Table Calculation Functions
- Window Functions
- Date Functions
- LOD-Level of Detail
- Types of Charts
- Dashboard Functions
- Dashboard Actions
- Data Modeling
- Tableau Server/Online
- Embedded Data Source
- Published Data Source
- Different site roles
- User controls
- RLS (Row level Security)
- Alert, Subscription, Metrics
- Empty Extract
- Real time Scenarios
- Dashboard Creation From Scratch
Course Name: SQL Tools: Oracle Topics:
- Tools: SQL
Topics
- Introduction to sql
- Introduction to databases
- Install a database engine
- Data types
- Operators
- Case manipulation functions
- Character manipulation functions
- Date functions
- Null functions
- Number functions
- General functions
- Aggregate functions/group
- functions
- Analytical functions
- Data definition language commands
- Data manipulation language
- commands
- Transaction control language
- commands
- Data query language commands
- Joins
- Constraints
- Set operators
- View
- Materialized view
- Sub-queries
- Pseudo columns
Course Name: Python
- Tools: Python
Topics:
- Introduction
- Literate Programming
- Anaconda InstallatIon Procedure
- Jupyter Notebook Environment
- Python Hello World (Print statement in
- python) Basics
- Strings
- Python Functions
- Conditional Statements
- Iteration
- Lists
- Tuples
- Dictionaries
- Packages and Modules
- Regular Expressions
- File Handling
- File Data Processing
- Sets
- Functional Programming
- Maps in python
- Filters in Python
- Lambdas in Python
- Numpy
- Pandas
- Matplotib
- Data Analytics/BI Developer Weekdays Training ( Morning, Day time & Evening)
- Duration: 40 Hrs
- Data Analytics/BI Developer Weekend Training (Saturday, Sunday & Holiday)
- Duration: 15 Weeks
- Data Analytics/BI Developer Fast Track Training
- Duration: within 20 days
Data Analytics/BI Developer Online Training in Tambaram
Greens Technology Tambaram providing best one-on-one Data Analytics/BI Developer Online training in Tambaram with Placement Assistance. Our trainers are conducting Data Analytics/BI Developer Training to students through TeamViewer, Skype, GoToMeeting Software. We also offering Online Data Analytics/BI Developer Fast Track Training with affordable course fees.
Data Analytics/BI Developer Corporate Training in Tambaram
In Greens Technology Tambaram, offering Data Analytics/BI Developer Corporate training in MNC Companies around the Chennai. We can take the Training for 15 to 20 employees in one Batch. Our corporate training based on updated Data Analytics/BI Developer Syllabus. Our Oracle Corporate trainers are specialized in their field and 10+ years of Experience in Oracle Platform.
Data Analytics/BI Developer Placement Training in Tambaram
We are offering Placement training for our students after completing the Data Analytics/BI Developer Classes. Our trainers are helps to attend the interview confidently. We are conducting resume preparation classes, Mockup Interviews, Aptitude Test.