Top 2 Data Analytics Courses In Guwahati With Placements

Data pervades our society and businesses today. It forms the lifeline of many gigantic corporations and networks. Google, Facebook, and many other brands of their caliber make big marketing and strategic decisions on data. Metrics derived from sources like satisfaction surveys, engagement levels, click-through-rate, etc. As organizations grow in size and diversification of work, they establish roles and departments to handle sections of the site that require a higher magnitude of care and consideration. Data analysts: educated by data analytics courses in Guwahati, fulfill the role of data manager for data-focused enterprises today.

Top Data Analytics Courses In Guwahati

The data analytics courses in Guwahati that inform and teach the basic actions of analysis to professional managers of big data should be scrupulously formulated and ardently conveyed to aspiring data analytics professionals. Now, this article caters to anyone who domiciles in Guwahati and feels a kinship to data. If you crave to learn the secrets of analyzing data so that corporations pay you lakhs of rupees for your incredible services, the recommendations we have garnered from across the Internet would fit you perfectly. 

However, let us not put the cart before the horse and tell you the means of learning a concept most effectively without the appropriate understanding of the concept beforehand. Prior research into a subject is salient and we believe in that aphorism fully. So, without further ado, let us begin to dismantle the concept of ….

Data Analytics and Its Procedures:

Data inspection, purification, manipulation, and modeling to uncover important information, support inferences, and aid decision-making.is known as data analysis. Data analysis is used in many corporate, scientific, and social science fields. It encompasses multiple procedures under several titles and has different dimensions and methodologies. In today’s corporate world, data analysis contributes to greater scientific decision-making and more effective business operations.

It is informed through many data analysis techniques that you can learn from the plethora of data analytics courses in Guwahati. Algorithms and mechanical processes have been automated through artificial intelligence to allow for the collection and organization of unstructured raw data. Data analytics aims to use this raw and unstructured data to facilitate business conclusions, support business decision-making, etc. Data analytics as a field includes various perspective approaches to solve and formulate data issues and problems of businesses and businesses working at large. These approaches are three in number, namely:

Descriptive Analysis: The analysis form of the simplest order, descriptive analysis is a simple method of analysis that works to establish a superficial relationship and causality descriptions. It points at various trends and the relations that relate closely with those trends, however, does not describe in detail the factors affecting these trends or any of the factors that allow for the formation of the relationship in the first place. It is a highly accessible tool of everyday use that utilizes the simplicity of popular software services like Excel and Google Charts. Majorly, the descriptive analysis focuses on relaying ideas and trends through effective communication and forms the jumping pad that allows for deeper insight analysis to progress decision-making.

An example of this analysis might be the reports of traffic and engagement that land on your homepage and interact with your content, ads, or website URL. All of these interactions can be tracked and compared to previously generated metrics to know the level of your engagement compared to historical data. Development of important business metrics like key performance indicators (KPIs) and fixation of return-on-investment valuations (ROIs).

Diagnostic Analysis: This type of analysis helps formulate answers to questions that form the reasons for trends and patterns in data. It answers why something happened the way it did and the underlying factors that influence it as well as the supporting factors of the trend/pattern. It is not only a means of affirming correlation among variables but also testing and examining the correct formation of a hypothesis and the various pitfalls concerning them. It is possible to investigate data sets’ patterns and connections through manual sorting and filtering of data, statistical methodologies, and automated algorithms as well. 

This process involves probing for data anomalies in a data set or market occurring due to extraneous factors that are out of any one person’s control. Furthermore, it includes the collection of data about this specific inconsistency or anomaly through various channels and sources, and statistical techniques are used for the interpretation of this anomaly and why they occur at all. 

Several concepts are ensconced under diagnostic analysis that needs to be understood to produce a good result that is useful for business decision-making. They are as follows:

Testing Hypothesis: It is the process of future or historically-oriented hypothesis examination that is purposed to determine the accuracy of the hypothesis to conduct research. The test deliberates over the accurate descriptions of terms used and the exact means used to prove or disprove the hypothesis. It may also lead to the revelation of faults in the hypothesis and ways to improve on them. 

  • Differentiating Between Correlation vs Causation – 

Relationships between variables can exhibit multiple natures depending on the way they influence each other. If the variables are independent but a change in one reflects some change in the other (positive or negative) It can be related to correlation. No value of change occurring in one variable reflecting in another refers to zero correlation whereas causation is an entirely different beast. It refers to two variables where a change in one directly affects another variable. The presence of any of these identifiers among variables can be an indictment for any professional who has learned from the best data analytics courses in Guwahati to know he must focus on these variables first. 

Regression Analysis: Analysis was done using statistical models and methodologies is required in some cases where trends and variables are not apparent to the eye of a trained analyst. Using some algorithms an understanding is gained of where explanatory relationships can be found for these variegated trends. For diagnostics, regression is used on historical data to gauge the current situation and whether the engagement or value we provide has surpassed or lagged compared to past estimates. 

Understanding customer behavior is a key tenet for most companies that focus on diagnostic analysis. These companies wish to deliberate on key components of products or services that optimally satisfy customer needs or drastically improve customer retention. Customer subscription models for companies like Netflix are based on honing their models to perfection for maximum retention and engagement with customers, asking for feedback about their experience regularly. 

Predictive Analysis: The meat and potatoes of the analysis process, predicting the trends of variable relationships through the creation of models and intricate algorithms that help in the developing of insights into future outcomes. Shortly following the development of insights comes an evaluation of the results and the steps that can be taken to upgrade efficiency or cut back on procedures that are inducing much higher costs on products or services. These can include sophisticated computer programming tools like neural networking software, multiple decision-making models, and statistical regression analysis. Modeling is a major component in the arsenal of this analysis that attracts clear and defined predictability into the analysis of a given set of business data.

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Modeling can be divided into three major types that can lead to better decision-making for effective product strategies and branding opportunities. These are:

  • Classification Models of Data:

These models are a formulation of highly supervised machine learning that generates outputs that base the input into distinct categories. These utilize historical data as a foundation and generate probability scores using neural networks and logistics regression analysis to lay data into distinct binary categories. This modeling operates based on a classification that demarcates the limitations and allowed operations of the model at hand. Classification helps businesses in minute ways that echo larger impacts on the efficiency of business practices.

  • Clustering Models of Data:

A form of unsupervised machine learning procedure that works on the principle of similar data points and sets being drawn together and dissimilar data points being distanced. Like an inverted magnet, clustering is founded based on collective attributes that are shared across data values. Grouping these values together and then generating effective ways to enhance each group’s interest by catering specifically to their needs adds a much-needed hint of personalization and creative expression that may exalt the user experience or marketing impression over the hill and straight into landing a new client. 

Clustering is done in many discrete fashions; expectation maximization and hierarchical clustering to name a few. 

  • Modeling Time Series: Models based on the timeliness of information based on scales like daily, monthly, etc. These types of models are utilized by seasonal organizations or rigidly scheduled organizations that work on noted cyclical behavior as a base. Discrete-time data mapping can help in denoting the important spaces of time where the bulk of value addition or data values are gathered, thus the cost-to-benefit ratio of a business or firm skyrockets. 

Few Details About the Process of Data Analysis:

Analysis levies a heavy duty of disintegrating the integrated into individual components that are thoroughly investigated in their form, composition, connection, and every remaining aspect of their existence. This initial exploration of data and its subsequent binding into a gallery with unique albums under the ultimate banner of an overarching hypothesis that is well represented by ‘to be or not to be in the words of Shakespeare, leads to the nurturing of business insights. If the data fails to conclude in the favour of the postulated hypothesis, then the hypothesis is whisked away to be altered and reintroduced into the process until the moment of acceptance and the business insights are developed. This process is rigorous and thorough, like the data analytics courses in Guwahati we will recommend to you.

 Data analytics courses in Guwahati don’t restrain themselves to brevity and dole out information to any paying hand and a willing ear. These data analytics courses in Guwahati dictate a standard procedure for developing business insights that need to be shared with you chronologically. These are:

  • Establishing Data Requirements
  • Collection of Data from Discrete Channels
  • Processing of Data
  • Cleaning/Scrubbing of Data Values
  • Models and Algorithms Used
  • The Utilization of Data Products
  • Presentation and Communication of Outcomes of Analysis

As per the instructions provided by the best data analytics courses in Guwahati, these steps are not absolute and can vary depending on the niches. Furthermore, they are flexible and require constant adjusting and correcting throughout the data analysis process. 

Before we dive into the best data analytics courses in Guwahati for a resident of Guwahati, let’s gain a better understanding of the place.

Guwahati- Gateway to Northeast India:

The City of Temples is a majestic piece of land situated in the Brahmaputra basin that blooms with vivid history and culture that is opposed to the booming industries and the rancor of one of the fastest-growing cities of the nation. The indigenous wildlife is unique and emanates the beauty of nature in animals like gigantic Asian elephants, rhinoceros, primates of all varieties, and endangered species of birds that have reigned on the horizon for centuries. However, with the inclusion of the city in the Smart City Initiative launched by the Government of India, and the enormous manufacturing industry in the region, the city is poised for the development of private ventures and enterprises.

This offers any data professional, especially one who has been taught by the best data analytics courses in Guwahati to cleave a space for earning lakhs while doing a job they adore. From the renowned tea industry to the refineries producing fuel and other products, data analysis can be crucial in inducing inexorable efficiency and profits, not only for public sector undertakings but also for private ventures and enterprises. Now that you have a clue of the benefits that good data analysis can accrue to your firm or business and a rudimentary comprehension of the methods of the data analysis process, let us dive into the best data analytics courses in Guwahati replete with curiosity and enthusiasm. 

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Best Data Analytics Courses in Guwahati:

1. Google Data Analytics Certificate by Coursera:

One of the best data analytics courses in Guwahati offered by Google leads you directly to informed and up-to-date learning of job skills that are in demand in the data professional industry. Skill proficiency in all the important procedures of data analysis such as data cleaning, visualization of data sets, understanding and dissecting big data coupled with the fine handling of programming languages like SQL, etc. It is a self-paced course that provides you with a world-class opportunity to work with real-time projects and like-minded professionals and instructors from your aspirational field of work. 

Important Features:

  • Beginner-Friendly and Easy to Understand
  • Variety of Monetary Options Available Including Aid, EMIs, Etc.
  • Very Flexible Self-Paced Learning
  • Google Professional Certification 
  • Coverage of All the Important Topics of Data Analysis
  • Opportunity for Real-Time Projects with Google Capstone

Modules: These are eight in number, namely:

  • Foundational Understanding of Data 
  • Questions and More Questions Lead to Decision-Making
  • Data Exploration
  • Data Processing: Inconsistent to Consistent
  • Analysis of Data to Answer Business Questions
  • Data Sharing Through Visualisation Techniques
  • R Programming: Its Value in Data Analysis
  • Google Case Study: Capstone Project (Real-Time)

Pricing: The pricing of this course is dependent on the type of learning duration you opt for:

  • 6-month – ₹ 574 per month
  • 3-month – ₹ 765 per month
  • 1-month – ₹ 1147 per month

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2. Data Analytics Graduate Certificate by Harvard Extension School:

This is one of the most professional data analytics courses in Guwahati that educates you on the best practices of the data analytic world by using real-world projects and instances to guide you in honing your skills as a data professional. It teaches you in-depth analytics to lay the groundwork for brilliant work in the development of data insights. Computational statistics, technologically advanced tools, and foundational systematic methods of analysis are all a part of the various applications of data analytics principles that you’ll be taught during this hybrid course. 

Important Features:

  •  Gain Incredible Amounts of Knowledge Regarding Data Visualisation & Analysis
  • Provision of Four Incredibly Valuable Certifications
  • Prestigious Graduate Credit 
  • Flexible Format Options
  •  Provision of Electives 

Modules:  This course is structured to provide you with a comprehensive and sublime learning experience. This course offers three entire sections of subjects to help you understand everything about data analytics. The three sections contain subjects with their respective syllabi, namely:

Other Courses in Guwahati:

Electives Subjects – Choose 2 or 3 out of the Following:

  • Understanding Computer Science and Python
  • Using Python and Java for Web Programming
  • Designing Databases and Developing them Using SQL
  • Analysis of Big Data 
  • Database Administration and Using Oracle
  • Healthcare Scenarios for Big Data and Machine Learning Processes
  • Business Data Mining Process
  • Real-Time Technology for Advertising and Further Analysis
  • Data and Remote Sensing Applications

Introductions – Choose 0-1 out of the following:

  • Quantitative Methodology for Economics and Finance: Introducing Basic Concepts
  • Quantitative Methodology for Humanities and Social Sciences: Introducing Basic Concepts

Compulsory Subjects – Choose 1 out of the following:

  • Statistical Modelling & Its Fundamental Concepts
  • Social Science and Quantitative Methods in Detail

Pricing: Since this is a globally renowned course the prices may be exorbitant for some, although there are plenty of options for financial aid and scholarships.

For three years of study – 1021425 INR 

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FAQs (Data Analytics Courses in Guwahati):

Q1. Which professionals utilize Data Analytics today?

You’ll find professionals galore who are using data analytics today. To use data analytics effectively you must have a solid understanding of data and its various structures, methods, and procedures. Data analytics is effectively used by a variety of professionals today. Some of them are as follows:

  • Marketers who create marketing plans based on customer data, industry trends, and performance data from prior campaigns are obvious candidates for data analytics benefits since they handle marketing initiatives that can be greatly aided by data insights.
  • Product managers analyze market, industry, and user data to improve their companies’ products, thus applying data analytics and its subset of methodologies in their daily job.
  • Finance specialists forecast their organizations’ financial futures by analyzing past performance data and industry trends to determine patterns of activity and forecast future market trends. This is streamlined if the specialist holds some knowledge of the processes and modeling techniques of data analysis.
  • Specialists in human resources and diversity, equality, and inclusion use data on employee attitudes, reasons, and behaviors to effect genuine change in their organizations. They accomplish this by gathering relevant data from employees and then using this data to generate satisfaction models to establish relationships and improve the overall work environment through prescriptive analysis.

Q2. What are some common problems that data analysts might encounter while conducting data analysis?

The problems that afflict a data analysis usually are concerned with different stages of the life cycle of data projects. No proper structure or warehouse of data, leaving no scope for the data analyst to analyze past trends. Data gathered from too many sources that do not fit well with the other sources is another common issue that requires data-cleaning procedures. The utilization of spreadsheets and no proper methodology or established ethics of the company may drain a lot of time for the data analyst. Insufficient data to render further analysis and incredibly tedious labor and activity affect the data analyst every day and can lead to burnout over a while. 

Q3. What are the most popular tools in the field of data analysis?

Data organization requires tools for clear and vivid data structuring. Google Sheets or Microsoft Excel are great tools for this area of analysis. Tableau and Power Bi are essential tools for data visualization for an analyst. Data analysis develops insights to be relayed to the responsible parties who can utilize them to improve their business efficiency. Other important tools for statistical analysis are Oracle, SQL, Apache Spark, KNIME, etc. 

Conclusion:

Data Analytics is a field of work that has only trended upward in recent years. It is a jack of all trades that acts as a subset of methodologies and concepts that are extremely useful in today’s day and age. Hopefully, we were able to convey the important data analytics courses that you can utilize as springboards to cultivate a successful relationship with data and analysis. 

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