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Tag: Big Data Career

3 Ways Big Data Can Influence Decision-Making for Organizations!

Posted on by Imarticus Learning

An enterprise or any organization collects a massive amount of data daily while performing its operations. This data can be in the form of customer information while making purchases, vouchers,s, and bills by manufacturers, viewership on the online portals, etc.

For an upward movement in the market, it is significant that this big data does not lie untreated in the systems of the company instead it should be worked upon and put to good use to increase the efficiency of the company.

To screen and filter the big data, data analysts are hired to convert that data into a useful piece of information. It may be likely to occur to you that how big data influences an organization’s functioning. There are some decisions that are largely based on big data.

Influence of Big Data on Decision Making of an Organization

In the following three ways, big data creates an impact on the decision-making and the overall performance of a company.

  1. Promotional enhancement through real-time data

Whenever you shop from a branded store, you start receiving emails about their offers which sometimes claim that some deals are exclusively for you. Do you ever wonder how they send personalized emails to every customer based on their interests and their shopping histories?

Big Data CareerThese all are some promotional activities which the companies do by making use of big data. Big data influences the decision-making of the promotional activities of a company.

By doing this, customers may feel informed through the brand and it is sometimes the biggest and the most important step towards creating customer loyalty and long-term relationships.

  1. Expanding Operations Without Spending Too Much

To initiate a promotional activity or a campaign to attract customers, some companies spend a hefty amount of money which may or may not turn out to be 100 percent successful. However, by making effective use of big data these expenses can be avoided. If you already know which customer tends to buy within a specific price range, personalized promotions through the internet become easy.

Big Data Career

Moreover, wasteful expenditure can be avoided to a great extent. Real-time data can prove to be beneficial in determining some major issues in a particular product or service.

Companies can appoint data analysts who can screen the real-time data and make necessary changes as and when required.

  1. Speeding the Action

Whenever a company launches any product in the market, it is always hard for the company to anticipate the response it may get. Supposedly, the customers have questions or certain queries about the product, taking some time to answer them might affect the overall image of the company as well as the product.

Big data helps to tackle this problem in real-time. Queries can be handled in seconds than wasting several minutes and replacements can be made in fewer days as compared to the time it used to take earlier. Big data has brought about a paradigm shift in decision making which has made customer dealing and answering queries a much simpler task.

Conclusion

With edge-to-edge competition in the market, it is significant for any organization that it makes effective use of big data in its favor.

Big Data Career

With the proper use of big data, companies can foresee and predict the future market for their products and services as well. The points mentioned above have presented a lucid picture of how important big data has become lately.

Big Data CareerA big data career can prove to be beneficial and is considered among the most demanded career options.

For big data training, you must check out the courses and professional assistance being offered by Imarticus learning.

What are the Big Data Use Cases That Explains Digital Transformation?

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The business world is transforming. Big data is influencing business decisions, marketing optimizations, business predictions, and day-to-day operations. Big data is expected to reach $300 billion by 2023. Though the term ‘Digital Transformation’ is loosely used as a euphemism for the modernization of data infrastructure, the true meaning of the word is becoming vital for the business world.

big data analytics courses in IndiaIt is true that the organizations are increasingly becoming data-centric, that they allot nearly 40 percent of their technology budget for digital transformation.

Data analysis courses facilitate faster, better, and smarter business decisions helping to achieve better operational efficiency, building a loyal client base, and leading to higher profit. Let us have a look at some use cases that explain this transformation.

Banking

Banks need to deal with a massive amount of financial information. Big data is used in banking to structure the collected data, organize them based on the business needs and analyze the data to derive insights on spending patterns, storing historical data like the transactions, payment records, etc. It also helps in identifying fraudulent actions and ensuring preventive measures are in place to block such frauds.

Another area of big data application is to prevent identity thefts. The banks use big data to keep a tab on customer actions. For example, if a customer follows regular spending patterns using the credit card such as groceries and general shopping, and all of a sudden there is a change in the behavior, such as spending money in gas stations and convenience stores from multiple locations across the city, the bank suspects something unusual. In this case, the bank may try to call the customer and find out if the card is stolen.

Online Shopping

Imagine you visited an online store and added some products to your cart. On second thought, you abandoned the cart and signed out without making any purchase. After some time, upon casual browsing, you see an advertisement for the same product you had planned to purchase.

The next day, you receive a mail with a discount offer for the same item. Targeted advertising is another application of big data. Online stores watch every movement of their customer from the moment they enter the store. They keep track of the pages you visited, the product you intended to buy by adding to the cart, etc. They use all this data to show targeted ads with irresistible offers that finally nudge you to purchase them.

Travel and Logistics

Big data facilitates the smooth running of logistics and transportation. It helps in scheduling flights, to show the booking status and seat availability, seasonal fluctuation in booking, etc. It also collects data regarding weather across the globe to predict flight delays. Big data is also used to analyze user trends and to predict the number of airplanes needed to cater to the increasing number of passengers. It could also be used to perform competitor analysis.

big data analytics courses in IndiaGiven above are some use cases that explain the application of big data in various industries. Apart from this, education, healthcare, digital advertising, environmental studies, human rights, etc. are some prominent areas that use big data to streamline their actions.

If you aspire to start a career in big data, this is the perfect time to enroll in a big data analyst course and secure a lucrative career.

How does Data Analytics help to Detect, Assess and Prevent Fraud in 2021?

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Fraud is a major problem in today’s digital world. Whether it is data analytics or data sciences, data analytics has become an integral component of fraud prevention. Data analytics is the process of data manipulation to identify patterns and predict trends based on data sets. The data can be in various formats like text, audio, video, images, or even data generated by sensors.

data analytics coursesIn simple words, data analytics is a data-driven approach to help you make better decisions. It helps organizations detect, assess, and prevent fraud in 2021. Data analytics courses are the latest trend among MBA students because data is so important to every aspect of life today.

This blog post will discuss how data analytics can help us detect, assess, and prevent fraud in 2021!

How does Data analytics help to detect, assess and prevent fraud in 2021?

In today’s data-driven world, data analytics has become an integral part of financial services. While data is not new to the industry, collecting and processing it at scale did pose a number of challenges in past years. However, with advancements in technology and data storage capabilities, data analytics as a tool for fraud detection has gained prominence within banks, especially after the 2008 economic meltdown.

Nowadays, organizations are generating large amounts of structured/unstructured data from various sources like customer service calls, social media platforms, etc., which can be analyzed using tools like machine learning, artificial intelligence (AI), predictive modeling, or deep learning algorithms, among others to predict potential threats on their business operations including risk management strategy thereby reducing operational costs & improving profitability by increasing revenue streams through better data-driven decisions.

However, data analytics is not just about data storage and analysis of unstructured data to identify anomalies within the data sets; it also focuses on methods that can be used by organizations to prevent frauds in real-time – a key area where financial institutions are looking at for growth opportunities as demand from millennial customers increases for mobile banking and increased online transactions via e-commerce portals among other channels.

In order to support their digital transformation journey & build a robust risk management strategy, banks and other institutions have started investing heavily into analytics capabilities by hiring data scientists and data analysts to leverage the power of data for fraud detection in real-time.

According to a recent report by MarketsandMarkets, the global data analytics market was valued at $16.06 billion in 2016 is expected to reach $73.47 billion by 2021, growing at a CAGR of 28% during the forecast period from 2017-2021.

Some key areas where data analytics is being used extensively include: 

Customer profiling– understanding customer behavior patterns using unstructured data sets such as social media posts or email communication logs;

Fraud Detection– monitoring transactions on data sources across data systems and data formats to identify suspicious activity;

Risk Assessment– showing the correlations among data sets of different entities within an organization or between organizations.

This is a great opportunity for anyone who wants to learn data analytics, as there are plenty of job opportunities for data specialists.

Learn data analytics with Imarticus Learning

Imarticus Learning offers data analytics courses in India that help professionals from diverse backgrounds understand concepts of data analysis. This course enables you to analyze large amounts of data using various methods such as statistical tools, pattern recognition, etc.

data analytics courses

Thus, you’ll be able to solve complex problems related to web intelligence, predictive modeling & simulation techniques or extract information quickly with minimal time lag through the Business Analytics course.

For more insight, connect with us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru Hyderabad, Delhi, and Gurgaon.

Analytics & Sports – How Data Analysts Be Asking in The Glory in The Sports

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Sports have seen their fair share of analysts and pundits ever since the first game was played. Traditionally, the analysis made by these pundits and analysts is based on hunches rather than concrete mathematical and statistical foundations. Even if they tried to factor in the statistics, there is no way that a human brain would calculate the entire complex, behind the scene calculation, which goes into a typical mathematical or statistical model.

So, it was thought that data analytics in the sector of sports had reached saturation. It all changed with Machine Learning and Artificial Intelligence.

In case you are not aware, machine learning and artificial intelligence are the fields that employ complex statistical models with a colossal amount of data to analyze the data, derive insights, and make predictions from it. So, when these advanced modeling techniques are fed the data generated from sports, we derive more accurate results, wisdom, and forecasts than all the pundits and legacy sports analysts.

Let us now see precisely what makes data analysis so lucrative in this sector.

How is sports analytics changing the paradigm?

There are only two ways in which sports analysis is being used in today’s paradigm. One is when the sports teams ask for data analytics, and the second is when it is used for sports betting.

data analytics certification course in IndiaThe first step of the Data Analytics course in sports involves mining various data like stats of any individual player, match conditions, and the teams’ recent performances. Then, all the information is passed down to Data Analysts.

It is their job to run machine learning models on this data to generate new insights. Now, these insights could be as simple as whether the team would win the next match or not.

To something more specific like, will Ronaldo be able to score his third goal with his left foot in the 69th minute?

Analytics is not limited to in-game events. By analysis of the data generated by the fans, the team would be able to cater to their needs better and thus improve their following. The sports team can also use data analysis to enhance merch sales.

How are big teams using data analytics?

While there are many examples available out there, we choose the ones from football.

Manchester United: We all have seen the Red Devils wear the AON branded shirts for a long time now. ManU has been using AON’s data analysis to stay ahead of the curve.

Real Madrid: This might come as a surprise to many, but Real Madrid has partnered with Microsoft (the Azure platform owner) to provide the Madridistas with all the analytics they need. They use Microsoft services to plan out the training, performance, and even fitness regimes of their players.

Conclusion:

There are a lot of apparent benefits when it comes to using data analytics training in the paradigm of sports. We have barely touched the surface here. However, we hope that we were able to provide you with some new information about data analysis in sports today.

What Is a Real-time Processing in a Big Data Use Case?

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Breaking down Real-time Processing

In today’s digital era, people are accustomed to real-time information that helps them make more informed decisions by factoring in the latest updates. Businesses in contemporary need real-time information to remain competitive in the market and improve their offerings.

best Data Analytics courses in IndiaLeveraging big data has become indispensable for businesses as it helps them provide valuable insights into the market. A big data career is also considered one of the most sought-after career choices given the demand for the same.

Real-time data processing systems help to factor in rapidly changing variables and relevant data to provide instant output so that any unnecessary delays can be avoided.

Some of the most prominent examples of real-time processing include order management for e-commerce websites, online ticket booking, financial fraud detection, radar range system, etc. A continuous stream of data is required to produce instant output in real-time. The most prominent benefit of real-time processing is that it helps to provide instant results and ensures that everything is up to date.

Real-time Big Data Processing Applications

Some of the most prominent applications of real-time big data processing in the contemporary include the following.

Online Commerce

Online commerce or e-commerce platforms heavily rely on real-time big data processing given the nature of business. It helps to solve issues related to customer service, inventory management, purchase pattern detection, personalized offerings, reduction of churn rate, etc. E-commerce companies also use real-time data processing to improve their logistics; they identify the nearest warehouse to effectively reduce delivery rates. It also helps to optimise the price and increase the sales volume by analyzing tons of data in real-time.

Social Media Networks

Gone are the days where people used to receive news the next day after the occurrence of a particular event. Social media networks have improved the flow of information and one can instantly receive any new update in real-time avoiding any delay in communication. Given the flow of information on social media platforms, real-time processing of data is almost a necessity. Some of the important functions performed by real-time data processing in the case of social media networks include classification of user-generated data or content, speeds up real-time trending, server functionality analysis, etc.

Healthcare

The healthcare industry also heavily relies on the use of real-time data processing systems. Some of the most common applications in this sector include real-time patient monitoring to assess crucial changes, wearable sensors and devices help to make life-saving decisions using real-time data. A majority of the data in the healthcare domain is usually unstructured and real-time big data processing helps to provide a detailed overview. It also assists in prescribing relevant medicines and avoids any unnecessary expenses.

Conclusion

Real-time big data processing has become popular in the last decade and is almost a necessity for a business that wants to create a sustainable brand in the long term.

best data analytics certification courses in IndiaThe big data career is also gaining traction with the growing demand for data analysts who can assist in the real-time processing of big data.

One can opt for data science courses from reputed institutions like Imarticus Learning to boost their job prospects and build a career in this field.

Most Essential Asset for Professionals: Data Analytics Tools!

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To perform data analysis, professionals use tools & software that ensure the best results. There are many of them in the market, but a few are on the top list for data analysts that need to be chosen wisely to extract the best benefit. 

This article discovers the best data analyst tools and highlights key features of each based on different types of analysis processes. But first, here’s a basic definition & introduction.

What Are Data Analyst Tools?

Data analyst tools are applications & software that data analysts develop & perform analytical processes to make better, informed business decisions while keeping costs low & profits high.

Top Tools Used by Data Analysts?

1. Business Intelligence Tools

BI tools are the most represented means to perform data analysis. Specialized in business analytics, they prove beneficial for every data analyst to monitor, analyze, and report essential findings. Self-service, advanced SQL modes, and predictive analytics make them easily adjustable to every level of knowledge without immense IT involvement. 

DATAPINE covers most requirements from beginners & advanced users.

Key Features:

  • Visual drag-&-drop interface
  • Powerful predictive analytics & interactive charts & dashboards
  • Intelligent alarms triggered for anomaly

2. Statistical Analysis Tools

There exist multiple programming languages that make work easier & effective. With the expansion of languages, some rules and scenarios need special attention for statistical data analysis & modeling.

R PROGRAMMING is the most popular tool for data analysts.

Key Features:

  • An ecosystem of more than 10k packages & extensions for data analysis
  • Statistical analysis, modeling, & hypothesis testing
  • Active community of researchers, statisticians, & scientists

3. General-Purpose Programming Languages

Programming languages help to resolve a variety of data problems. Tools like C#, Java, PHP, Julia, Ruby, and Python are many reliable solutions.

PYTHON is the most trusted tool.

Key Features:

  • Open-source solution with simple coding processes
  • Easy integration with other languages
  • Advanced analysis processes through ML & text mining

4. SQL Consoles

SQL is a programming language used to manage data held in relational databases, effectively handling structured data for analysts. Highly popular in the data science community, these tools are used in various business cases & data scenarios. 

MYSQL WORKBENCH is the most popular one.

Key Features:

  • Unified visual tool for data modeling, administration, SQL development, backup, etc.
  • Instant access to the database via Object Browser
  • SQL Editor offers color syntax highlighting, reuse of SQL snippets, & execution history

5. Unique Predictive Analytics Tools

Predictive analytics is an advanced technique to combine data mining, AI/ML, and predictive modeling to predict future events. It is an essential data analysis tool as it simplifies predictive analytics processes. 

SAS FORECASTING is an analysis software helpful for predictive analytics processes & helps analysts to predict future scenarios.

Key Features:

  • Automatic forecasting for entities or products, including hierarchical forecasting
  • Scalability & modeling to create an ensemble
  • An unlimited model repository including time-series & casual methods

Apart from the tools mentioned above, there are industry-specific analytics tools & data science platforms that assist professionals. A business analytics course can help you better understand what data analytics is!

Build New-Age Career with Imarticus:

data analytics coursesImarticus Learning offers Data Science Courses, the most extensive, industry-approved experiential learning program ideal for Data Analysts. 

Industry experts have developed the programs to help students learn real-world applications of Data Science from scratch & build robust models to generate valuable business insights and predictions.

Take a giant career leap with this analytics program.

For more details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

Augmented Analytics: The Future of Data & Analytics!

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Augmented analysis simplifies data analysis and helps in getting insights. It is used by firms/companies to forecast better and to automate data analysis processes. Augmented analyses use enabling technologies like AI and machine learning to help speed up and automate data analysis processes.

You can manage your business data up to an extent when the data generated is large one needs augmented analysis to manage big data sets and extract insights. Less time will be spent on understanding the data with the help of augmented analysis. Let us see how augmented analysis is the future of data & analytics.

Benefits of Augmented Analysis

The pros of augmented analysis are as follows:

  • You can automate data analysis processes like data cleaning, forecasting, data management, etc. with the help of augmented analysis.
  • Expert developers can build better business models with the help of insights via augmented analysis. The accuracy of predicting trends and business opportunities increases.
  • Data preparation under which the data is classified and arranged in a structured manner is a very tedious chore. This process can be automated via augmented analysis.
  • The augmented analysis will help you in cost optimization as it will help you in using less human labor and more automation. Your developers can provide you with more insights with the help of augmented analysis.
  • Risk identification and management can be done properly with the help of augmented analysis.
  • Data insights can be represented in natural language statements to people who are not into data analysis. In organizations, augmented analysis helps in conveying business insights and forecasting results to all employees.
  • Data security and privacy can be managed better via augmented analysis. Any anomaly in the data set can be identified immediately and can be managed. It also helps in adhering to data regulations laid by the regulatory authorities.

 Why Big Data Management is Necessary?

The augmented analysis helps in big data management as such a large amount of data cannot be managed manually. Big data management is done by firms to know about market trends, opportunities, market volatility, etc. It also helps in knowing about the buying habits of customers/clients. You can target an audience of any particular age group, locality, gender, by using data insights. You will stay ahead of your competitors and grab potential opportunities.

big data analytics courses One can learn big data management via Big Data Analytics Course from a trusted source like Imarticus Learning.

Data Analytics Future

The latest technologies like machine learning, deep learning, AI, etc. are shaping the way the data analytics industry worked.

Companies and firms are producing more data every day and a lot of businesses are shifting online, to manage this data augmented analysis is being adopted by firms. Developers can boast a more successful Big Data Analytics Career via augmented analysis as it will increase their analytics ability.

Conclusion

Data analytics is one of the fastest-growing sectors recently. Companies and firms are investing in data analytics to gain profits in the long run. One can learn from Big Data Analytics Courses available on the internet to build a successful Big Data Analytics Career. Grab your online course now!

Understanding the Role of Data Analytics for E-Commerce Success!

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The demand for data analytics in e-commerce is on the rise. Data analytics is a key tool for understanding the behavior of your customers and prospects, allowing you to make data-driven decisions. Data specialists have a promising future in this industry, and companies are clamoring to find talented individuals who can help them better understand their consumers’ desires.

The increased use of data analytics will be pivotal for businesses that want to stay competitive in today’s marketplace. This blog post will discuss how data analytics can help e-commerce businesses succeed in today’s competitive marketplace.

Role of Data Analytics in E-commerce Success

Data analytics plays an increasing role in e-commerce success. Companies are looking for data analysts with the skills to help them gain a competitive advantage by understanding customer needs, behaviors, and trends within their industry. More specifically, companies rely on data analytics professionals to find:

  • Targeted customers that they would not have reached otherwise
  • Deep insights into areas such as product development and merchandising
  • Actionable information on factors such as click rates or session times across devices (desktop vs. mobile) can be used to improve online conversion rates

In addition, these new positions require individuals who can communicate effectively throughout a company’s hierarchy—from senior management down to marketing teams—to ensure all stakeholders have access to the information they need to make informed decisions.

Data is also playing an increasing role in offline commerce. The challenge of understanding customer behavior across channels has led to the increased demand for data analysts with a comprehensive view of all aspects, including brick-and-mortar retail and online sales and promotional efforts.

A growing number of companies are seeking specialists who can collect, cleanse, manage and analyze large amounts of disparate datasets at scale, helping them gain insights about their customers that were previously hidden or difficult to address.

Companies have access to more sources than ever before—from internal company databases such as CRM systems (customer relationship management) and ERP systems (enterprise planning) through social media platforms such as Facebook or Twitter. In addition, companies are finding new ways to interact with their customers and gather data through mobile apps and other interactive tools that enable them to obtain information about customer preferences (e.g., location) in real-time.

What kind of skills are required to succeed as a data specialist?

For a successful data analyst, it is important to have strong analytical skills. You need to ask the right questions and then find and understand relevant information (data). Some of the other qualities that are needed include:

  • Ability to work with large datasets
  • Attention to details
  • Analytical thinking rather than creative thinking
  • Ability to identify patterns
  • In-depth knowledge of statistical concepts like standard deviation, correlation, and regression analysis.

Have a promising data specialists career with Imarticus Learning

Big data analytics courses in IndiaImarticus Learning offers a data analytics certification course that prepares you for a high-growth career. Our unique combination of analytics courses helps students build strong foundational skills and practical industry exposure to build a successful career in the field of Data Science and Business Intelligence.

This course is developed and taught by industry experts with significant experience in analytics. It includes a range of topics, from basic statistics & probability theory to advanced machine learning techniques. This course will help you move forward in your career!

For more details, contact us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru Hyderabad, Delhi, and Gurgaon

What is Big Data Analytics?

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Big data can always be related to massive volumes of data generated directly by the company or acquired from various sources. However, in order to truly utilize the data to its full potential, companies are always in dire need of skilled data analysts or business analysts. Big Data Analytics allows companies to use this data to their advantage by gaining valuable insights from this data, thus making more effective data-backed decisions.

Data Analytics Certification Courses with placement in IndiaThe Big Data Analytics course positively affects sales, decreases risks, optimizes production, helps understand customer behavior, and even allows companies to come up with more efficient marketing strategies.

This is all possible due to Big Data, Data Science, and analytics. Budding analysts are always advised to join well-orchestrated Data Science courses in order to acquire the skills required to effectively analyze the data.

The true intention of Big Data Analytics is always to promote more efficient use of resources and getting better results through data-centric suggestions from business analysts. It is highly recommended to opt for reputed business analytics courses in order to productively contribute to this field. Constructing data-based predictions is the key to making businesses run adequately.

Why is Big Data Analytics Important?

Fundamentally, Big Data Analytics allows companies to discover patterns, trends, and correlations from massive amounts of data. This allows companies to use the newly acquired information to their benefit, thus making more effective business decisions, increasing profits, and satisfying customers better.

From helping in marketing campaigns to improving production capabilities, Big Data Analytics can help with any sector that generates data. Analytics help companies make customers happier through understanding customer behavior and trends better.

Fintech courseData scientists and analysts help companies massively cut down operational costs by resources much more effectively. Decades back, even though “Big Data” did not exist, business analytics did. However, it was not a cost-effective process and demanded a lot of time.

Big Data Analytics online training allows data scientists and analysts to make this process much faster. With the advent of AI in analytics, Big Data Analytics can almost provide real-time insights from incoming data.

What is Data Science?

The value Data Science brings to business analytics is immense. It is responsible for everything in the process. Starting from sourcing the data and modeling it to the time that the required insights are acquired, Data Science powers it all. Data Science allows companies to effectively source transactional or raw data from various sources and then process it. This is where analysts come into play, they analyze this data and then help companies visualize the data.

What are the requirements to become a Data analyst?

How to become a data analyst? It might sound complex but it is truly not that hard. There are many good Data Science courses or business analytics courses available online and offline that one can choose from. However, care must be taken when choosing a Data Science course in India or outside, ensuring that you get the best out of your time and energy. Any good Data Science course in India will cover the fundamental skills required to become a data analyst and prepare students to effectively use analytics tools when working with Big Data or data in general.

 

Conclusion

Big Data makes it possible for organizations to store and harness the capabilities of massive amounts of both structured and unstructured data. Even though what Data scientists do is similar, Big Data Analytics requires exceptional skills when working with large volumes of data. A good Data Science course in India is highly recommended such as this PG program in order to gather the required skills to work with Big Data and Analytics.

Related Article:

What is the difference between data science and data analytics?

Take Advantage of This Once-In-A-Lifetime Opportunity To Express Your Ideas And Win Fantastic Prizes.

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Are you a Data science blogger? Imarticus Data Science is proud to announce our Data Science Blogging contest. This contest will reward the best Data Science blog posts of 2021 with fantastic prizes with up to 10,000 gifts vouchers.  

Do you feel like you have many insightful thoughts to share as a blog on Data Science & Analytics? If you enjoy writing about data science, there is a once-in-a-lifetime opportunity to put your ideas in front of countrywide audiences. And the best blog post author stands to win a prize for their work!

data science and analytics blogging contestShare your blog on any of the following topics: 

  • Data science
  • Data Analytics
  • Machine Learning
  • Data Engineering
  • Deep Learning
  • Computer Vision
  • Python Programming and many more related to Data Analytics topics. 

 The Criteria to Participate in Data science Blogging contest

  • All blogs should be 500 to 1000 words in length.
  • The content must be original, well-researched, plagiarism-free, and informative.
  • Do not entertain duplicate posts.
  • The deadline is August 31st, 2021, at 11:59 pm IST.
  • The number of article contributors is restricted to three members.
  • blog.imarticus.org will host all the articles with credit given to the contributor(s). Blog entries are considered Imarticus Learning intellectual property from this point onward.

 How to enter in the Data science Blogging contest and the process

  1. Write a blog on a topic of your choice pertaining the data science and analytics. After completion, share your blog at blog@imarticus.com on or before August 31st, 2021, 11:59 pm, Indian Standard Time (IST).
  2. The originality, creativity, and level of depth in all blog articles.
  3. The content should meet the minimum criteria explained above and be submitted before the given deadline.
  4. Will upload all the eligible blogs on or before September 11th, 2021.
  5. The writers will receive the respective blog links by September 11th, 2021. The individual should share the blog link on their social channels with mandatory hashtag rules.
  6. Imarticus team will evaluate the engagement on the individual blog posts until September 30th, 2021. The Imarticus panel team will shortlist the best 25 blogs and promotes them on their social channels until October 30th, 2021.
  7. The blog that receives the most engagement by October 30th, 2021, is shortlisted as the winner. Imarticus Editorial Panel’s decision is final and binding in case of any dispute.data science and analytics blogging contest

 Why should you participate in the Imarticus Blogger of Year Contest?

  1. Imarticus Social recognizes your skill and is eager to help promote your blog.
  2. Exiting winning amount to motivate and encourage your effort.
  3. The winner details will get necessary coverage within the media promoted and supported by Imarticus Learning.
  4. We will promote the interview of the top 25 selected bloggers on different social channels of Imarticus Learning. 

Apart from the 10,000 gift voucher to the winner, Imarticus Learning will give prizes to the other participants. The details are as follows:

  • Winner: 10,000
  • Runner Up: 7,500
  • 3rd Place: 5,000
  • 4th to 10th Position: 2,000
  • 11th to 20th Position: Imarticus Hall of Fame Entrydata science and analytics blogging contest

T&C Apply.
Imarticus Learning shall own the Intellectual Rights of the blog content shared with us at blog@imarticus.com with due credits to the writer(s) till perpetuity. Imarticus Learning reserves all the rights to use, publish or remove the content on all our platforms.

The decision of the Imarticus Editorial Panel shall be final and binding in all matters. Any dispute will fall under the jurisdiction of Mumbai. The winners will receive Gift Vouchers.
To know more – Click here 

Conclusion: 

If you are interested in data science and want to share your ideas with the world, then this is a once-in-a-lifetime opportunity. Entering our #ImarticusBlogLikeAPro Season 1 Championship Award along with a cash prize of INR 10,000/ will not only is fun, but it could also win you fantastic prizes! Professional tone required for submission.