Data Analytics course in Dehradun
Are you looking to advance your career and improve your data analytics skills? Our data analytics course is the only place to look!
In this comprehensive course, you’ll learn everything you need to know to become a skilled data analyst, including data manipulation, data visualization, statistical analysis, and more. Our experienced instructors will guide you through real-world examples and provide you with hands-on practice to help you build your skills and confidence.
Whether you’re just starting out in the field or you’re looking to upskill, this course is designed to help you succeed. With our flexible learning options, you can take the course online at your own pace or in a classroom setting with other aspiring data analysts.
Investing in your data analytics skills can pay off in a big way, with high-demand careers in fields like finance, healthcare, marketing, and more. Don’t miss out on this opportunity to improve your career prospects and set yourself up for success. Enroll in our data analytics course today!
It’s an approach that brings together the best of talent and the best solutions.
Vistashikha solution pvt ltd wing Vista Academy provide training to Uttarakhand youth in the field of Data Analytics and Data Science and .
Vista Solutions also provide solutions to its clients.
Its an approach that the bring to gather the best career creating top and the best training.
Vista Academy is a prime institute in corporate job training providing job training in Data Analytics Course With Excel, Tableau, SQL & Power BI
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What does the course offer?
The Data Analytics Course covers technologies like Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R & Python. Apart from the theory classes, there are hands-on assignments and projects that help you apply the concepts that are learned by a student.
Python programming
Python programming is the most popular and powerful programing language used nearly in all AI and machine learning operations. It is a highly sought-after skill by software professionals, app developers and beginner programmers. This powerful object-oriented programming language is featured with high extensibility, large standard library, portability and embed-ability making it popular in domains of data analysis and visualization, AI and machine learning, application back-end framing, desktop app development and much more.
R programming
R is a dominant open-source programming language in the field of data analysis, statistics and data visualization. The ability to provide high-end support to statistical and graphical techniques such as linear/ nonlinear modelling, time-series analysis, clustering and many more, makes it highly extensible and popular amongst data analysts and data scientists. Used for statistical computing, R language helps in effective data manipulation across enterprisess.
Microsoft Excel
Microsoft Excel is an important tool for data analysis. It helps companies accurately assess situations and make better business decisions.
Data analysis is the process of cleaning, processing, and analysing raw data in order to extract useful, relevant information that can help businesses make better decisions. The strategy reduces the risks involved with decision-making by providing useful insights and facts, which are frequently displayed as charts, photographs, tables, and graphs.
Data analytics includes data collection, organisation, storage, and the tools and techniques used to delve deeper into data, as well as those used to convey the findings, such as data visualisation tools. Data analysis, on the other hand, is concerned with the transformation of raw data into relevant statistics, information, and explanations.
Tableau Analytics
In this Tableau blog, you’ll learn about what Tableau is, what it is used for, how Tableau works, and so on one by one from scratch. Tableau software is one of the fastest growing data visualization tools which is currently being used in the BI industry. It is the best way to change or transform the raw set of data into an easily understandable format with zero technical skills and coding knowledge.
Tableau is a full-featured data analytics platform that lets you prepare, analyse, collaborate, and share big data insights. Tableau is a leader in self-service visual analysis, allowing users to ask new questions of managed big data and quickly share their findings across the company.
PowerBI
Power BI. Unify data from many sources to create interactive, immersive dashboards and reports that provide actionable insights and drive business results.
Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights.
Microsoft Power BI is a suite of business intelligence (BI), reporting, and data visualization products and services for individuals and teams.
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SQL
Structured Query Language (SQL) has been around for decades. It is a programming language used for managing the data held in relational databases. A data analyst can use SQL to access, read, manipulate, and analyze the data stored in a database and generate useful insights to drive an informed decision-making process.
SQL is widely used by software engineers, but it’s also popular among data analysts for several reasons: It’s simple to grasp and learn from a semantic standpoint. Analysts don’t have to copy data into other programmes because it can access enormous amounts of data immediately where it’s kept.
power bi and tableau courses
Explained Architecture and Features Power BI and Tableau are two popular Business Intelligence (BI) tools for collecting, integrating, analyzing, and presenting business data. They help you in performing data analysis, data manipulation, and visualization of data in order to understand and derive conclusions from company data.
CAREER & SALARY
Experience plays a deciding role in finalising the salary of a data analyst. One’s experience in the field depicts more extensive knowledge, practical solutions, agile working and leadership skills to train others. Therefore, an analyst in the industry for more than three years will have an increased payment than the salary of a data analyst for a fresher.
The average pay structure for data analyst based on experience is as following:
Entry Level (> 1 yr of experience) – ₹342,363/yr
Early Career (1-4 yrs of experience) – ₹422,408/yr
Mid- Career (5-9 yrs of experience) – ₹690,734/yr
Experienced (>10 yrs of experience) – ₹942,653 to ₹1,750,000/yr
Data Analyst Salary: Based on Location
The salary of a data analyst for a fresher might be different if located in Mumbai from the data analyst salary in Bangalore. This is because the location is among one of the factors affecting the data analyst job salary.
Every city or state has a different cost of living and demand of the profession and accordingly the pay is decided.
Job Roles in Data Analysis
Job Roles in Data Analysis
Marketing Analyst
Business Intelligence
- Analyst
- Research Analyst
- Operations Analyst
- Risk Analyst
Growth of data
- With the rise of various social media platform and multinational companies across the globe the generation of data has increased
- Data has grown vastly on the last decade and expected to reach 175 zeta bite in 2025 according to international data corporation.
- Companies are on the lookout of professional who turns raw data into crucial insight. Hence there is and there will be a constant demand for professional in this field.
- Organization are lookout for such candidates.
What is data analytics ?
- Analyze means of scrutinized something to find our meaningful conclusion from it.
- Data analytics also work similar. It is the process by which useful insight are extracted from raw data.
- By studying and examining carefully this insight are important for business trends, market innovation and market trends profit loss report etc.
- Data analytics is the term as the process of extracting meaningful insight such as hidden patterns, market trends, and customer preferences are done by the study of procured data. Example converting jig saw puzzle into beautiful pictures.
- This information can be converted into graph and chats which provides precise result of the analysis.
- Various technologies tools and framework are used in the analysis process.
- The organization takes the benefit of data analytics to convert the raw data into meaningful insight.
- Therefore, there is high requirement of skill in data analytics.
Raw data to meaningful insight
Job role in data analytics
- There are many job roles that can be taken up by fresh candidates.
- It is a lucrative field as the role of data analytics only going to continue to blossom in the years to come.
Who is data analyst ?
- A data analyst is a professional who works on collecting, processing and analyzing a large dataset.
- Static analysis is done on various data.
- Every business generate data be it marketing ,sales ,research , customer feedback,customer behavior, logistic and transportation.
- A data analyst will take this data and take various measures such as how to price new product, how to cost cutting ,how to innovate better products.
Responsibilities of data analytics
- Gather information
- Gather information form querying and also maintain and design database.
- Data analytics write complex SQL queryines and script to gather and extract information
- From several databases and data warehouses.
- Mining Data is mine from various sources and then organized in order to obtain a new information from it.It is vital role of data analyst.
- Data analyst collect data from various sources and work on it.
- Now with this data, we can use a model for it and reduce complexity and increase the efficiency of the whole system.
Tools
- Use various static tools and programming language for analytical and logical examination of data.
- Using different libraries and packages data analysis discover trends and patten from complex data set.This help them to find more unseen insight from the data to make business predictions.
Preparer summary report
- Prepare a summary report for the leadership team.
- This is done with the help of data visualization.
- So that they can make timely decisions.
- Data analytics use multiple data visualization tools.
Skill required
- Hold a degree or even Intermediate.
- Knowledge of language of language like R ,Python and java script.
- This will help you solve complex problem
- You should have experience with data bases and data analysis tools.
- Knowledge of MS Excel ,Matlab SQL queries etc.
- Should have understanding of statistics and machine learning.
- Experience of using several data visualization tools.
- Good presentation skills.
Average annual salary
In US 45000 $ – 83000$
In India 400000 – Rs 1000000
Companies hiring data analytics
- Amazon
- Microsoft
- Wall mart
- Paytm
- apple
Why to do Data analytics training ?
Why everybody should learn data analytics
There’s no doubting that analytics isn’t only the way of the future; it’s also the way of the present. Analytics is currently employed everywhere from airline route planning to predictive maintenance analysis in manufacturing plants, having been adopted in a wide range of industries. Even industries that would not be associated with big data, such as retail, are adopting analytics to boost consumer loyalty and personalize unique offerings.
1. Analytics professionals are in high demand.
This apparent increase is due to a growth in the number of companies employing analytics and, as a result, needing analytics people. According to research conducted by QuinStreet Inc., the trend of implementing big data analytics is expanding and is regarded as a high priority among U.S. organizations.
2. Massive Jobs Available & Bridging the Skill Gap.
The need for analytics specialists is rapidly increasing, yet
3. Salary increases
Data Analyst Salary at Entry Level: In India, an entry level Data Analyst/Scientist can earn roughly Rs 507,269 per year. Salary for Data Analysts at the Junior Level: Junior Data Analysts make an average pay of Rs 9,21,957 per year if they have at least two years of expertise in the industry. there is a huge supply shortage. This is happening all around the world and is not limited to any particular region. Despite the fact that Big Data Analytics is in high demand, there are still a big number of unfilled positions due to a shortage of essential skills around the world.
4. Working flexibility in any industry.
You’re not normally confined to working in a specific area as a data analytics professional, which can be a significant benefit. Data analytics is beneficial to every industry. Financial, healthcare, retail, logistics, and human resource management are some of the major industries where data analytics professionals are in great demand.
5. Advances in practical knowledge
Learning from industry specialists who have worked in the same sector for years is one of the most rewarding aspects of the process. You will have the opportunity to learn and work with commonly used marketing technologies.
Can a Fresher Become a Data Analyst? Entry Level Data Analyst Jobs
We have a lot of data, but we don’t know which of it is valuable. To extract insights from this enormous data, organizations need qualified professionals—data analysts. A data analyst’s job is to transform data about a company’s customers, goods, or goals into information that decision-makers can use.
Businesses can use the data analysts’ findings to personalize items for customers, develop marketing strategies, and improve the manufacturing process significantly. Whether you’re looking for entry-level or senior-level data analyst positions, you’ll always have to work with data. This post will cover how to find entry-level data analyst employment, as well as whether or not a fresher can work as a data analyst. Let’s get going.
JOBS FOR ENTRY-LEVEL DATA ANALYSTS
A bachelor’s degree is required for most entry-level data analyst positions. On the other hand, a master’s degree in data analytics is useful. Most persons with technical backgrounds start their careers as statistics assistants, business support analysts, operations analysts, or other entry-level positions, where they obtain crucial on-the-job training and experience. What talents, on the other hand, will help you land an entry-level data analyst position? Let’s take a look at the qualifications for entry-level data analyst jobs.
BASIC UNDERSTANDING OF EXCEL TABLEAU
You should be familiar with Microsoft Excel if you want to work as an entry-level data analyst. A data analyst’s responsibilities include categorising data and computing numbers. As a result, knowing how to use Excel is advantageous.
Good statistical knowledge: Statistics and distributions, which are critical in data analysis, should be well-understood. For an entry-level data analyst position, you’ll need a strong understanding of inferential and descriptive statistics, binomials and tests, and experimental and statistical design.
FAMILIARITY WITH MACHINE LEARNING:
In the field of data analytics, programming skills are essential. You should be able to interpret data using programming languages as a data analyst. For an entry-level data analyst position, you should be proficient in at least one programming language. The more languages you know, however, the better. SQL, Python, R, C++, Java, MATLAB, and PHP are some of the programming languages used in data analysis
Overview of the course:
Participants will do this course with advanced skills in Excel, Power BI, SQL, and Python data analytics. The course has a strong emphasis on practical application through projects, internships, and resume development in addition to technical understanding. Participants will receive instruction on how to build their resumes for data analytics careers, gain practical experience, and create a portfolio of data analytics projects.
Data Preparation and Analytics Introduction
- Process overview for data analytics
- Recognizing data forms and kinds
- Methods for transforming and cleaning data
Excel for Data Analysis
- Week 1: Introduction to Excel for Data Analytics
- Week 2: Essential Formulas and Functions
- Week 3: Data Cleaning and Transformation
- Week 4: Data Analysis with PivotTables
- Week 5: Advanced Data Analysis with Excel Functions
- Week 6: Data Visualization Techniques
SQL for Data Analytics
Week 1: Introduction to SQL and Relational Databases
Week 2: Retrieving Data with SELECT Statements
Week 3: Joining Data from Multiple Tables
Week 4: Aggregating Data with GROUP BY and HAVING
Week 5: Subqueries and Derived Tables
Week 6: Advanced Querying Techniques
Week 7: Modifying and Updating Data
Power bi for Data Analytics
Week 1: Introduction to Power BI
Week 2: Data Connection and Transformation
Week 3: Data Modeling in Power BI
Week 4: Data Visualization with Power BI
Week 6: Advanced Data Transformations and Modeling
Week 7: Power BI Data Sharing and Collaboration
Python for Data Analytics
- Week 1: Introduction to Python for Data Analytics
- Week 2: Data Manipulation with Pandas
- Week 3: Exploratory Data Analysis with Pandas
- Week 4: Data Visualization with Matplotlib and Seaborn
- Week 5: Advanced Data Manipulation with Pandas
- Week 6: Statistical Analysis with NumPy and Pandas
- Week 7: Data Analytics Projects and Case Studies
Machine Learning
- Week 1-2: Introduction to Machine Learning
- Overview of machine learning concepts and applications
- Supervised, unsupervised, and reinforcement learning
- Week 3: Data Preprocessing
- Data cleaning and handling missing values
- Feature scaling, normalization, and transformation
- Handling categorical variables
- Week 4-5: Supervised Learning Algorithms
- Linear regression
- Logistic regression
- Decision trees and random forests
- Week 6: Support Vector Machines (SVM) and Naive Bayes
- Understanding SVM and its applications
- Introduction to Naive Bayes classifiers
- Week 7: K-nearest Neighbors (KNN)
- Understanding the KNN algorithm and its use cases
- Week 8: Model Evaluation and Selection
- Training, validation, and test set splits
- Cross-validation techniques
- Performance metrics for classification and regression models
- Week 9: Model Optimization and Hyperparameter Tuning
- Grid search and random search for hyperparameter tuning
- Regularization techniques for model optimization
- Week 10: Ensemble Methods
- Introduction to bagging and boosting techniques
- Random Forest, AdaBoost, Gradient Boosting
- Week 11: Introduction to Deep Learning
- Neural networks basics and architectures
- Convolutional Neural Networks (CNNs) for image analysis
- Week 12: Model Deployment and Advanced Topics
Project , Resume building, and Interview preparation
- Week 1: Introduction to Project Building in Data Analytics
- Week 2: Data Collection and Preparation for Projects
- Week 3: Data Analysis and Visualization in Projects
- Week 4: Project Documentation and Presentation Skills
- Week 5: Resume Building for Data Analytics Roles
- Week 6: Resume Optimization and Tailoring
- Week 7: Interview Preparation: Technical Skills and Case Studies
- Week 8: Interview Preparation: Behavioral Skills and Mock Interviews
Data analytics classroom courses
Experience the power of data with Vista Academy’s in-depth data analytics classroom courses, which are created to give you the skills and knowledge you need to extract useful data from large, complicated datasets.
Experience the complexity of data preprocessing, statistical analysis, and data-driven decision-making through engaging classroom sessions at Vista Academy, led by experienced instructors.
Discover the art of storytelling with data through Vista Academy’s data analytics classroom courses, where you’ll learn to effectively communicate complex findings using powerful visualisations and compelling narratives.Join our data analytics classroom courses at Vista Academy and embark on a transformative journey to become a proficient data analyst, gaining hands-on experience in data collection, analysis, visualisation, and machine learning.
Data analytics classroom courses from Vista Academy provide a well-rounded curriculum covering important subjects like exploratory data analysis, statistical modelling, and machine learning, enabling you to take on real-world data difficulties head-on.
Final Thoughts
If you’re serious about pursuing a career in data science and Analytics, there’s no better time than now to acquire your data science certification and make a strong impression on potential employers.
This course overview offers a basis for creating projects, creating resumes, and preparing for interviews related to data analytics. Depending on the participant’s ability level and time limits, instructors can change the pace, depth, and extra topics. To enhance the learning process, practical exercises, mock interviews, and feedback sessions might be included.
After finishing this course, participants will have experience working on real-world projects, have a resume that is attractive for data analytics positions, and be ready for data analytics interviews. They will be equipped with the knowledge and self-assurance to successfully advertise their capabilities, improving their prospects of success in the competitive employment market.
Learn Data Analytics from experts and attain a Data Analytics Certificate
COURSE DURATION
8-12 MONTHS
FOR PROFESSIONAL PROGRAM IN DATA ANALYTICS
8 MONTH FOR MASTER PROGRAM IN DATA ANALYTICS
Admission only on appointment
Yes we provide placement support.
No online training
Many firms in India hire data scientists and data analytics professionals at all levels, from entry-level to executive. Amazon, Flipkart, Accenture, IBM, and Juniper Network are some of the top data science and data analytics recruiters.
- Salary
- Massive adoption of Data science
- Easy to Start
- A Demanded Profession
- Various job titles and responsibilities
- New Skill
- Opportunities
- Due to digitization, there is an opportunity for growth.
- Engage as a Stakeholder
- Opportunities in a variety of industries and domains
- Key Decision-Making Power
- Improve the relationship between the retailer and the customer
Anyone with a structured thought process, logical thinking skills, and a willingness to acquire new tools, as well as a sound business perspective, can enter the field of data science and data analytics.
It is not necessary to hire great coders or highly knowledgeable individuals.
- Visualization Specialist
- Machine Learning Expert
- Analytics Consultant
- Solution Architect
- Big Data Solution
- Business intelligence specialists
- Big Data Analyst
- Data scientist
- Database Administrator
If your are Not Curious
If you are Not Motivated.
If you can’t dream and Visualize .
Don’t Need to Apply
Measure Students on job skills, personality and fit
Proper screening of students are done throughout the course and these screening are shared with companies and finally you fit to get the job .
To prepare you for a job, we focus on practical and personalised learning. For real-world skills, the most up-to-date curriculum, expertly structured project work, and extended post-session support are provided, making it well worth your money.
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If you’re serious about pursuing a career in data science, there’s no better time than now to acquire your data science certification and make a strong impression on potential employers.