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Tag: big data analytics career

How big data analytics is used in social media

Posted on by Imarticus Learning

Almost all of us are familiar with social media in 2021. There are many social media platforms run by different companies in the world. Not to forget, the large number of social media users that have been added in recent years. With the rise of social media, the amount of data produced by different platforms is unmatchable. The likes, shares, and comments across social media platforms contain information regarding user behavior.

It is why business organizations are using big data analytics to make the best use of the data available on social media platforms. Big data analytics is widely used in social media to shape marketing strategies and much more. Read on to know seven ways how big data analytics is used in social media.

  • Omnichannel presence

Many business applications and websites have a social media integration. Customers can log in to a business application using their social media credentials. It helps businesses to collect customer data from social media platforms and use them to provide better services. You can get access to social media posts, browser history, and much more. Since customers have an omnichannel presence, you can collect data from all sources to know more about the preferences of customers.

  • Real-time activity monitoring

Social media is a place where you immediately get to know when someone has liked a post or shared a product link. Businesses monitor the activity of customers on social media to know about their current mood. If a social media user is liking your product posts, you can show them an email quickly to convert them into a customer. No other platform can inform customer preferences in real-time other than social media. Big data is used extensively to collect real-time activity reports on social media.

  • Forecasting

When big data is mixed with modern-day technologies like ML and AI, it can predict customer preferences. Based on customer habits on social media, AI/ML algorithms predict their demands. Businesses then focus on releasing new products/services as per the future demands. For example, when a customer buys something online, the chances of them buying similar products increase.

  • Security

Data vendors cannot illegally transfer customer data to the wrong hands. When customers share data on social media, that data can only be used for business purposes. Your social media data cannot be placed in the wrong hands by business organizations. Big data is used for enhancing the security of social media platforms based on customer suggestions.

 

  • Campaign monitoring

 

Marketers run social media campaigns to boost their ROI (Return on Investment). Using big data, marketers can know how well a social media campaign has performed. Young aspirants can go for big data training to know more about how to run social media campaigns and study high-end analytics.

 

  • Product pricing

 

When a firm launches its product on social media, customers give their valuable opinions. Social media is widely used to determine whether customers are satisfied with the pricing of a product or not. Big data training includes data collection from social media channels and how to analyze them.

 

  • Ad creation

 

Social media is used to collect info about customer preferences. Based on that info, targeted, and personalized advertisements are displayed on social media channels. Technologies like Hadoop programming and Python programming are also used by big data analysts in social media.

Young aspirants can go for the big data analytics programs launched by Imarticus Learning. Its PG Program in ML and Data Analytics can help working professionals in getting a raise. Start your big data course and learn Python and Hadoop programming!

What is the best approach to Data Analysis in 2021?

Posted on by Imarticus Learning

As time goes by the approach to any form or strategy of business changes. Even more so when it comes to data, as it is ever-changing. Throughout the years, data analytics has grown from a peripheral part of a business to an integral part of it. It is a prominent tool to not only extract and decipher past records but also predict and develop future strategies.

However, it comes with a little difficulty as most of the time, data analysts have little idea of how to execute a business. And in the same way, executives have little idea of how data analytics works and how to use it.

This is why it is important to have a basic idea of what is business analytics to give you that little edge over others. The best way to do this would be with a data analytics certification course, similar to what Imarticus Learning is providing with their new PG program. However, to make it easier, here we have compiled two successful ways that data analytics can be approached in 2021.

For the long run

In many cases, companies invest a lot in data analytics and focus on building business value around it. This includes training the employees about data analytics, developing company systems and syncing them with data analysis, and finally, discussing more data analysis initiatives. This requires a complete transformation of business values and systems.

Tackling clearly-define high-grade problems

One of the best ways to approach data analysis is by defining a high-grade problem with clear goals. When it comes to high-grade problems, the issue remains in the volume or layers in which a problem is divided. Each of these layers interplays and pile up to end up being a high-grade problem.

So, with data analytics, you can target a small subset of the problem and by getting the numbers right, you can take a sustained route towards growth. Unlike the investment model where too much time could pass before results show, this model seems clearly the best approach in 2021.

Things to keep in mind

One thing to always keep in mind is that data analytics merely show a record of how the past has been and how the future can turn out to be. It is not always possible to meet the exact expectations as the results depend on a variety of things. There are a few other things that everyone should keep in mind when it comes to data analytics, such as:

  • Data analytics need to be made a part of the main wing of a business as without being in the loop it would be impossible for the analytics team to be of any help.
  • Problems should be specified and addressed together with the executives. This will make the process of extracting and deciphering data as well as developing a proper plan to address the specified problems a lot easier on both sides.
  • Executives should have a basic knowledge of what is business analytics. It will make the communication and understanding between the two teams smoother.

 Conclusion

 The process can create disruptions as data tends to create transparency. It can be uncomfortable to face the shortcomings of a business, however, this is also the best way to form strategies to overcome those shortcomings. This is why companies need experts on their teams to help them along the way. You can enhance your skills with a proper data analytics certification course or a PG program if you wish to pursue this career.

Why Is It So Easy To Get an Analytics & AI Certification, But a Struggle To Get The Right Job Interview Opportunities ? Imarticus Has an Answer

Posted on by Imarticus Learning

The data science domain is expanding. With it, the demand for AI, ML, NLP, and other data science careers is also rising. Reports suggest that there were 2.9 million data science job openings in 2019 alone and by 2026, this number is going to go up to 11.5 million.

Despite this huge demand, getting a good job in the AI and Analytics field is a real struggle. Many aspiring people do many courses in different branches, be it computer visions or deep learning. But when it comes to securing a job, a lot of them find it extremely difficult.

Key Reason for Difficulty in Job Seeking

While most of the people blame it on the companies that they don’t understand what they want, the harsh reality is that most of the aspirants in this sector lack the important skills required to get a good job interview opportunities. Many candidates are not competent enough to grab a job role in data analytics or the AI field. Data science is a complex field that requires an extensive amount of knowledge and a high-level skill-set.

Though many students do certificate courses from various institutions online, most of the time they do not get taught and trained the right way. It results in students missing out on important concepts, analytics, and numerical aptitude. When these students go out in the real world, they end up facing rejection on their job applications.

The thing is if students want to build careers in the data science field, they need to be exceptionally well at it. For this, they need to pursue a course that builds their foundational and advanced knowledge in-depth and provides them with the crucial practical skills required in the real world.

Imarticus Learning PGA – The right way

Imarticus Learning offers a Post Graduate Program in Analytics & Artificial Intelligence that teaches the in-demand tech skills in the job market at present. The teaching method involves engaging videos, live sessions, and exercises.

data analytics courses in IndiaIndustry professionals having years of experience in this field deliver ML, computer visions, and deep learning training projects.

Upon completion of the post-graduate program in data analytics course, Not only but students also get guaranteed job interview opportunities and placements in leading companies.

The PGA course covers theory and practical learning on the following subjects:

  • Data Science Fundamentals
  • Deep Learning
  • Machine Learning
  • Computer Visions
  • Natural Language Processing
  • Placement Preparation

During the entire duration of the course, students are provided with a mentor who supports them in their academic journey and guides them in their career path. The mentor performs the following roles:

  • Motivate and Inspire to engage in projects and their completion.
  • Monitor your grades and potential.
  • Build meaningful connections that will help you beyond the course.

By studying the PGA course with Imarticus Learning, students get complete support and guidance throughout their learning process. The career services provided with this course include:

  • Guaranteed Jobs
  • Resume Building
  • Interview Preparation
  • Profile Enhancement

Job Roles after PGA Course

Upon successful completion of the Imarticus Learning PGA course, you can find suitable careers in:

  • Business Analyst
  • Artificial Intelligence Engineer
  • Data Analyst
  • Machine Learning Engineer
  • Data Science/Machine Learning Consultant
  • Web & Social Media Analyst
  • Machine Learning Architect
  • Data Scientist

The salary packages in these job roles are quite lucrative. The average pay scale in Analytics & AI roles is around INR 5 LPA to 25 LPA.

Joining Procedure of PGA Course

Candidates interested in Analytics & Artificial Intelligence can join this program for building a successful career in this field. The joining procedure is simple and includes three steps:

  • Detailed Profile Check
  • Online Tests
  • Enroll

The prerequisites for the course include a graduation degree with a minimum of 60% and a basic understanding of mathematics and programming. With data analytics course, students can get the best education and make their dream of becoming a professional in this field come true.

How Can Data Analytics Help You Become a Better Entrepreneur?

Posted on by Imarticus Learning

The data analytics industry has grown exponentially in the past decade, and more data is being generated every day. This is due to the increasing need for data and data analysis that companies are facing as their dependence on data increases exponentially.

This data, when analyzed, can be used to make important decisions for businesses and individuals alike. Data analysts not only have a skill set that can be applied to any business but also possess the ability to think critically and identify innovative solutions for problems.

The time is now for you to join a data analytics course so you, too, can reap the benefits of this thriving industry! Let’s see how.

How do Data Analytics Skills Help you Become a Better Entrepreneur?

One of the important skills for entrepreneurs is knowing how to handle data, i.e., learning data analytics skills. These skills are very versatile and practical that will enable you to handle your business & its data efficiently. Data analytic skills have not only increased in importance over the last few years but also have grown to be one of the leading industries, so it’s no surprise that individuals who know data analytics skills are in demand and have a lot of career opportunities.

Data analytics skills give you a new way to compete in the job market, one that does not hinge on your education or even some sort of innate talent. There’s always a need for more data analysts and statisticians as businesses are coming up with ways to mine their databases for insights. Nearly 50% of Data Scientists say they created statistical models last year despite having no formal training in statistics.

best data analytics courses in IndiaLearning how to efficiently analyze large sets of data can help make you stand out from other applicants who might have an impressive resume but lack experience with big data tools like Excel and R programming language.

Employers know there is value in someone who has the ability to work quickly through raw information without any previous knowledge about what it all means, which makes learning Data Analytics an attractive option for students and professionals alike.

Data Analytics skills can help with this by providing an easy-to-read breakdown of campaign success and failure rates. This will allow you to take action on your most profitable campaigns while cutting funding for any that are not profitable.

best data analytics courses in IndiaFurthermore, it can help you by providing reports on the time spent on each campaign or task that will enable you to measure how much effort is put into work. Thus, learning how to utilize data analytics training can help you become a better entrepreneur by learning what actions need to be taken or prioritized differently in order to grow your business more effectively.

Become a New-Age Data Entrepreneur with Imarticus Learning

If you want to be a better entrepreneur, it is time for you to join the Data Analytics course at Imarticus Learning. The data analytics course at Imarticus Learning is designed to keep the specific needs of today’s data-driven world in mind and will teach you the skills that can help make your business more successful.

best data analytics courses in IndiaThe curriculum includes a range of topics, from basic statistics and probability theory to advanced machine learning techniques. You can learn data analytics online at your own pace, so there’s no need to put off enrolling until you have more time or money!

This program will help you move forward in your career! For more details on Data Science Course, contact us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Edge Vs Cloud: Which Is Better For Data Analytics?

Posted on by Imarticus Learning

What is Edge Computing?

Edge computing is a segregated topology which serves to bring processed information closer to the device that is gathering the data rather than relying on a central unit which would be located much farther away.

What is Cloud Computing?

Cloud computing involves the process of delivering important information and services such as storage without the need for involvement of active management.

Which Out of the Two Is Better For Data Analysis?

In today’s world where AI has become an extremely important part of our lives, developers are looking to merge the devices we use on a day-to-day basis with artificial intelligence to make running businesses easier for organizations.

In such cases, we must look at the various computing methods that can make this possible in an efficient manner. Here, you would think that cloud computing would hold an important position in making the most suitable and ideal decisions. Platforms which are based on cloud allow developers to quickly create, deploy and handle their applications.

These would include playing the role of a platform of data for applications, application development which would help bridge the gap between data and users, and so on. It is popular for its flexibility with data storage and the ability to perform analysis processes.

On the other hand, edge computing allows applications and various other analytical and service processes of data to be done away from a central data unit, bringing it nearer to end-users. It allows the processing to take place within the locally available resources, thus bringing it a step back from the intricately planned cloud model where data processing happens in specific data centres.

Let us dive into this further in detail.

Cloud vs Edge Computing: Latency Problems

Cloud computing is used extensively across various organizations and companies for data analysis. However, there may be situations where a business may face problems in collecting, transporting and analysing the data given.

Edge and cloud computing for Data AnalyticsWhen data is transferred to a remote cloud server, it allows the user to perform various complex algorithms with machine learning and thus predict the maintenance needs of a particular section. This is then forwarded to a dashboard on a personal system where one can determine what decisions are to be made further. This is all done comfortably from home or the office.

This is great, however, as one begins to increase the intensity of operations, one may begin to run into issues such as physical limitations on the bandwidth of the network and thus also latency issues.

Edge computing does a great job at reducing latency issues by involving a local server, maybe even on the device itself. The only difference here is that the issue with latency is solved at the expense of the processing power offered by cloud computing methods.

Businesses, with edge computing, are now being able to decrease data volumes which would need to be uploaded and stored in the cloud. This thus makes the process of data analysis less time-consuming.

Edge computing may still interact with other website applications and servers. It includes physical sensor thus allowing it to help run smarter algorithms and facilitate real-time processing which is used in smart vehicles, drones and smart appliances. It may not be as strong as a remote server, but it helps reduce the bandwidth strain that one would normally face with cloud computing.

Data Analytics CareerA big data analytics courses would help equip a person aspiring to work in the field of data analysis with all the information that would be necessary. A big data analytics career is a good option because it is an ever-expanding field with a large number of opportunities!

How Do I Start a Data Analytics Study?

Posted on by Imarticus Learning

Before commencing anything new a lot of questions and queries baffle the mind. When starting a data analytics study there are some factors one must keep in mind for a smooth and practical flow of the study. By investing some of the time in the beginning to follow these steps, a good amount of time and efforts can be saved while carrying out the actual study.

Keep the following points in mind before kick-starting a data analytics study.

  1. Understanding the Capacity: Before you begin to explore a particular study in data analytics, it is significant that you know about the whole capacity of data analytics.
    Data Science Online Course
    There is going to be a great requirement of the theoretical knowledge and deep insight about data and understanding data. Learning about the coding languages and syntax is paramount to make a hold on data analytics.It can prove to be advantageous if you take up a data analytics course online which can make you learn data analytics and its different elements in a precise and detailed manner. You may refer to Imarticus learning which can help you hone your undiscovered skills and make you a genius in data analytics.
  2. Experimenting: Once you gain proper knowledge about the coding languages and their systematic usage, it is really important that before you jump on to the main data analytics study, you apply what you have learned by the way of an experiment. Internet is filled with data published by various renowned companies which can be used for the experimentation. Experimentation is the only means which can help you establish a relation between the cause and the effect.
  3. Specifying the Pre-requisites: Once you are done and satisfied with your experimentation, to begin the actual study in data analytics you need to specify the requirement of a specific date on which the research is going to be based. This data can be in any form like the number of people from the general population or the number of people working from home etc. Understanding the specifications of the data, in the beginning, is paramount.
  4. Collecting the Data: After specifying the requirements of data and recognizing the sources of that data, the collection has to be started. Data can be availed from various sources like the company portals or the organizational databases.The collection of data has to be appropriate and methodical so that it is not hard to decipher when the study begins. Sometimes the data collected is not at all in a usable manner and has to be filtered on various levels before beginning the actual study. In such a scenario, the data undergoes a processing and cleaning process.
  5. Processing the Data: For better understanding, scattered data has to be represented methodically for the study to be smooth. In this step, various tools are used to make the data workable. With the help of bar-graphs, tables with rows and columns, data are presented systematically. Generally, the use of spreadsheets is done for a structured display of data.
  6. Cleaning the Data: At this point, still, there would be a lot of information which is going to be of no use while carrying the study. There are chances that there is a duplication of the data. Most of the times there are certain errors in the data which may cause a lot of problems while studying and analyzing it. Such errors are got rid of in this cleaning process.

After following these steps, the study of data analytics can be taken forward in a hassle-free and smooth manner. To learn data analytics and how to communicate the data after analysing it, refer to Imarticus leaning which is an ideal way to learn data analytics through professionals.