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Tag: career in data analytics

Data Analytics in Healthcare: Can a Techie Succeed in The World of Medicine?

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In the modern-day, Information Technology has seeped into all sectors. Industries have adopted Data Science and Analytics to drive their work and have reaped the rewards for it. In the paradigm where Data Analysts are highly sought after in all sectors, how do they fare in the field of Healthcare?

 

Big Data Analytics courses are the perfect way for techies to break into the medical sector. It has become a tool with unlimited potential, and a Data Analytics career in healthcare is a very real and prospective opportunity.

Data Analytics is generally used to draw meaningful interpretations, find trends and predict possible outcomes from Data.

Healthcare Analytics specifically aids in avoiding preventable diseases, conducting an accurate diagnosis, predicting and combating epidemics and coming up with effective treatment strategies for diseases.

A Healthcare Analyst contributes to improving the quality of healthcare and reducing the treatment costs by automating tedious processes.

Applications of Data Analytics in Healthcare

There are many applications of Data Analytics in healthcare, and a career in the field works to implement these uses. Some of the most popular applications are:

Patients’ prediction: Healthcare Analytics can be leveraged to improve patient predictions. The past admission records can be used to discover hospitalization trends, peak times and deploy personnel accordingly.

Strategic Planning: The existing data can be used to identify patterns, conduct studies and map out strategies for extensive care and in community medicine.

Electronic Health Records:

It is one of the most popular uses of Data Analytics in Healthcare. It is used to track patient medications, treatments, progress, and medical history. Data Analytics on these can reveal more details about their medical conditions and lead to more accurate prognoses.

Predictive Analytics: Predictive Analytics is the practice of recognizing patterns and predicting probable outcomes by studying the data presently available. This can be used to improve care delivery for patients with complex medical history by using history to try and predetermine the conditions they may face in the future.

Data Analytics Careers in Healthcare

The applications of Big Data analytics in medicine are vast, and more are being uncovered every day. In this scenario, techies are being welcomed into the sector with open arms. Healthcare employs techies as Data Analysts, Informatics Consultants, Clinical Data Managers in the Quality and Performance improvement sector.

One can also get promoted to leadership positions for other Analysts as Informatics Director or Chief Medical Information Officers. All these positions come with their responsibilities as well as perks. The roles and responsibilities would also entail assistance in the proper integration of data analytics within specific healthcare areas.

Conclusion

A career as a healthcare analyst is a door that opens infinite possibilities. Not only do you get to save lives as a part of the field, but you also get to innovate and change medicine in your way.

How COVID-19 Is Revolutionizing the Indian Analytics Industry?

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As India recovers from the deadly second wave of the COVID-19 pandemic, the country is witnessing a first-hand revolution in demand for data analytics as a solution and its various use cases. An industry that has come to fruition over the last 7 years has steadily been gaining the attention of the masses; however, after the pandemic, experts are taking note that the importance and popularity of data analytics as a career choice will increase exponentially.

A recent report published by Analytics India Magazine shared that the Data Analytics Industry earned a total revenue of 35.9 bn USD as of March 2020, signifying a sharp increase of 19.5% over and above the past year. The report went on to highlight the fact that Data Analytics as a solution will encompass 35% of all IT solutions in India by the end of 2025.

This and data from several other peer-reviewed sources point at the steady growth this industry is witnessing in India, making it an ideal choice for those who are looking to foster a career in data analytics both as a novel approach or as career advancement and transition.

But what changed in the industry, and why are experts predicting an increased demand in this domain?

To put it simply, over the past couple of years, companies across all industries have slowly made the transition from guesswork to predictive analytics, which empowers them to foster key decisions by analyzing past market trends.

Although this industry was witnessing steady growth over the past few years, the onset of the pandemic put it into perspective for many, how important it is to expertly analyze the data we collect and take note of key dynamics and trends which will influence consumer behavior for days to come.

For instance, before the pandemic, data harvesters rarely focused on the movement data they collected from consumers, as use cases of these are yet to be pinpointed; however, as the nationwide lockdown started, it became abundantly clear to key stakeholders that expertly analyzing movement data can not only help them track the spread of the pandemic, but also equip them with key insights in terms of precautionary measures to be taken.

However, this use case would not have been possible without the intervention of advanced data analytics engineers from the best firms in India, thus contributing to the rising demand for talented professionals in this field.

Data Science Course

The Way Ahead

After the US, India is set to be the next battleground for developing a state of art data analytics hub, and several key observers of the industry have taken note of this fact. With the rising demand for data analytics as a solution among both public and private entities, there has never been a better time than this to foster a career in data analytics.

Coupled with the rising demand, there are now more resources available for those willing to learn data analytics and foster a future career which is immensely rewarding across multiple verticals.

All you Need to Know about Python and being a Certified Professional!

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Programming has always been the core of computer science and Information Technology. Every year millions of programmers graduate with degrees to look for employment opportunities. Therefore, the demand for programmers has grown exponentially, and the trend will not be out anytime soon.

Python is one of the most familiarly used programming languages and was released by Python Software Foundation in 1991. In a fraction of years, it gained popularity and was started being used as a programming language in various disciplines.

Python Programming Defined:

Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, drone systems, AI, robotics, developing cyber-security tools, mathematics, system scripting, etc.

Python ranks second among other programming languages. Imarticus Learning has some fascinating advanced-level courses on Python and data science, covering Machine Learning and Artificial Intelligence using Python. With expertise in python programming, candidates can start learning advanced-level Python libraries and modules such as Pandas, SciPy, NumPy, Matplotlib, etc.

Python Programming Career Options:

Python programming coursesAfter a course in applied data science with python specialization, you can choose several career paths. Some are stated below:

Data Visualization with Python and Matplotlib: The profile is linked with extensive data analysis, which is a future for the IT industry.

Web Programming: As you know, python is a concise language; many things can help you build a career as a web programmer.

Developing Games: If you are passionate about gaming and wish to develop games as a career someday, you need to put in efforts to learn Python and how to develop games.

Analyzing Data with Python and Pandas: This allows you to pivot into data science.

Why Python for Data Science?

The first benefit of data science using python is its simplicity. While data scientists come from a computer science background or know other programming languages, many belong to backgrounds with statistics, mathematics, and other technical fields. They may lack coding experience when they enter the field of data science. Python is easy to follow and write, making it a simple programable language to start and learn quickly.

There are numerous free resources available online let you learn Python and get help from communities. Python is an open-source language and is beneficial for data scientists looking to learn a new language because there is no up-front cost involved. This also means that many data scientists are already using Python, so there is a strong community for better guidance.

Python is especially popular among data scientists. There are many python tutorials and python classes where the world comes together to share knowledge and connect. Countless libraries like Pandas, NumPy, and Matplotlib available in Python for data cleaning, data visualization, data analysis, and machine learning make tasks easy.

Build Career in Data Science with Imarticus Learning:

Python programming course

Imarticus Learning offers some best data science courses in India, ideal for fresh graduates, professionals, and executives. If you wish to fast-track your Data Science career with guaranteed placement opportunities, Imarticus learning is the place you need to head for right away!

Industry experts design the programs to help you learn real-world data science applications and build robust models to generate valuable business data. Students go through rigorous exercises, hands-on projects, boot camps, hackathon, and personalized Capstone project, which prepares them to start a career in Data Analytics. Send an inquiry through the Live Chat Support System and request virtual guidance to commence the transforming journey!

Top 7 Reasons to Convince You To Take on that Data Analytics Job

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It’s more than just a buzzword, it’s a revolution– data analytics is here and here to stay. For four years in a row, data analytics was ranked the best job in the U.S. alone by Glassdoor in 2019. The data fever is catching on in other parts of the world too, as global economies become more interdependent and related.

More and more companies and industries are embracing data analytics, not least because it’s a science that delivers valuable insights applicable across all plans including business and marketing.

If you’re still hesitating about whether to go for a career in data analytics, allow these top 7 reasons to convince you:

#1: It’s in demand

Data analytics is one of the most in-demand jobs in the world today. This is because all industries need data-driven insights to make even changes, be it to pick a marketing option during A/B testing or rolling out new products. Data analytics is a high-skills, high-stakes job, which is why companies are ready to hire those willing to think creatively and derive data-based solutions to business problems.

#2: It’s easy to start

Educational institutions and course providers have sat up and taken notice of the demand for data analysts, leading them to introduce related training courses. Regardless of whether you’re a fresher or a professional in the tech field, data analytics training can help you start from scratch and build a portfolio of projects to showcase your skills These courses also provide tutorials in essential data analytics software such as Hadoop, Sisense and IBM Watson.

#3: There are plenty of job roles

Within the data analytics field, there are job roles that span academic divisions and aren’t restricted to engineering or software alone. Data scientists, systems analysts and data engineers will benefit from a background in the aforementioned academic fields. However, statisticians and digital marketing executives can look into roles such as quantitative analysts, data analytics consultants and digital marketing managers to put their skills to good use.

#4: The pay is good

The average salary in the data analytics field is US$122,000– a testament to how in-demand the profession is and how in dire need companies are of skilled employees. The figures vary depending on the role and job description but suffice to say that the pay is often much better than other technical jobs that people still seem to hover to by default. It’s also dependent on what industry you will work for, in what capacity and towards which goals.

#5: Growth opportunities abound

Technology is a dynamic field and with new changes come the chance to upskill, pick up new software and contribute to futuristic projects. Data analytics professionals can find themselves growing through roles and projects, oftentimes being tasked to lead a team or be the sole owner of a large-scale project.

#6: Industries are interwoven

With other tech fields, you might be restricted in your tasks or limited to a company. In data analytics, however, you get to pick and choose the fields you want, whether pure tech or even retail. Data analytics is in use across most industries so, once you find your niche, you’re ready to start dabbling in the industry of your choice.

#7: Influences decision-making

If you’ve ever wanted to be part of the larger organizational or business structure and contribute positively, chances are data analytics might be the niche for you. The insights that emerge from analyses of data can power strategies and create new business plans. This way, your contribution leads to progress on an organizational scale and your work can make or break a business.

Data analytics gives you the opportunity to become a more active stakeholder and contributor to any business regardless of the industry, so take the leap today.

Top Reasons Why Big Data Analytics Is One of the Best Career Moves!

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Reading Time: 3 minutes

What is Big Data?

We are living in an era where we consume data more than anything, be it food or water or even electricity. If you use technology to help yourself in your day to day chores or if surfing the internet to find information for your purpose is an on-going thing, you are one of the beneficiaries of the big data.

So what exactly is the big data? In the most basic sense, big data can be understood as the collection of data that is extremely large in size and is accumulated on a continuous basis.

Big Data AnalyticsIf we go by the general definition of it, the big data is an industry that deals with systematic extraction and storage of information in the form of data from various data points; it also helps to perform complex analysis of extremely large data sets.

The data stored is used to perform analysis to identify patterns, trends or establish association and relationship among different variables especially relating to human behavior and interactions. Examples of some big data sets include data generated by the stock exchanges, social media sites, etc.

Many big corporations are using big data today to gain customer insights and design their policies and price their products accordingly to gain maximum output from their investment on customer acquisition and other areas.

Big data analytics as a career option

In the contemporary world data is the fuel for exponential growth. Corporations today use data in conjunction with other progressive technologies like the machine learning and artificial intelligence to help process large piles of information and gain valuable insights from the same. The new technologies not only help to do too much in too little time but it also minimizes the chance for random human error, which is very likely when dealing with an extremely large amount of data set.

Since the big data is a fairly new field, very little is known about the career options and the work required to build a career in the domain. If we were to compare it with traditional occupations that are held in high regard, data analysts have a similar role to play as the doctors in our lives. Basically, they are the doctors for data, who help to analyze and scrutinize data and find any anomalies if they exist.

Big Data Analytics CareerThe most important factor why big data analytics is a good career option can be understood through the lens of general economics.

At present the demand for data analytics professionals in the industry is higher than the labor supply for the same, this means that it’s not only a growing field but also the one with higher perks and remuneration.

According to IBM reports the jobs in the data industry in the US alone will increase to 2720000 by 2020, higher than the current supply of professionals in the field. A career in big data is the most sought after especially in the developed economies.

According to sources, the current size of the analytics market is around one-tenth of the global IT market and is assumed to grow and become one-third of the global IT market in the coming years, another reason why it’s a good career move.

Finance and Analytics online coursesThe number of job posting on some of the reputed job portals has also shown a significant increase from the previous year indicating high growth in the field.

Big data analytics adoption is growing with the minute, another important indicator that favors the career move in the data industry is the increase in companies that are adopting big data analytics to improve their day to day functioning and cut their costs on futile marketing and advertisement.

The use of big data helps to make things more contextual for the customers and optimize the output and price for the brand in the process. The big data course is designed to help develop a comprehensive understanding of the subject and is beneficial for those who are eying for a career in this field.

Data Analytics: Expectations vs Reality

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Data Analytics: Expectations vs Reality

As we see the field of data analytics getting to its peak in terms of career choice, hordes of young people and professionals now want to make their careers in this field. However, data analytics like any other field is not everyone’s baby. It can be a suitable career option for people, who love data, play with figures and are comfortable in handling a wide array of analytics tools that play a vital role while treading this career path. In other words, you must be aware of the myths and reality about this domain, or else you end up messing up your career and start cursing your fortune.
Why is Data Analytics a hot choice?
Of late, the number of young professionals working in different domains has developed an affinity towards data analytics. Some of these have shifted from their career in IT and other fields towards it, while there are many who despite not knowing what is analytics are thinking for a change in their job. Thanks to a growing number of data analytics courses online, more and more people are thinking to take a shift to this career. There are primarily two key reasons to get attracted to this field:

  • It is a lucrative industry to join
  • It can give good salaries and perks if you have a passion for numbers

However, most of the people who do not even know the data analyst meaning still want to enter it. Hence it is imperative to be realistic at this juncture when you are thinking of taking a shift to this field.
Data Analytics – Reality & Expectations
Although the career in data analytics can be lucrative, if it is not your cup of tea, there is no point in heading in this direction. First of all, check these realities:
The deeper you go, the tougher it becomes – Career in Data Analytics can be a lucrative option and could be selling like a hot cake but the deeper you dig, the harder it becomes. Learning and mastering the concepts of data analytics is not often an easy job, you are supposed to be committed and have the knack to play with numbers and play with data. You should own and hone analytical, technical and personal skills. The day you stop studying the concepts and ideas of this field, you just end up becoming obsolete very soon.
Meritocracy – This field is for people who are known for their merits and credentials. You may find it easy to join any data analytics courses online, but if you cannot excel in it, you may end up finding a clerical job in any data science company. You have to be the best in your work, and there are reports of people joining by being a blind follower. Instead, you should be realistic in choosing this career. An average understanding and competence in this field will not let you anywhere.
IT can Tough and Frustrating – Being a Data Analysts is like a software engineer who also has to keep on updating and upgrading himself to survive in this tough world. It can be a frustrating experience for many despite putting so many years and money as an investment as what you get would be too little to celebrate. Having said that, if this career is not addressing your Why, then you are bound to feel its toughness and end up leaving it out of frustration. Unless you are very sure about this career and have the knack and passion for playing with data, numbers, and analytics tools it’s naïve to even think of entering into this field. The field of data analytics is very demanding; you have to be a consistent learner with focus and then only harnessing the best opportunities in this field is possible.
Conclusion
With the rise in demand for data analytics in the market, there seems to be a craze among the youngster to enter into this field. However, it is always recommended to check the reality and expectations of this field and then decide to move ahead. After all, it is naïve to enter into this field if you do not even know the data analyst meaning.

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The Complete Guide on Choosing The Best Data Analytics Course

Posted on by Imarticus Learning
Reading Time: 4 minutes

Are you interested in data analytics and application and data analysis tools? Well, just having an interest in this field will not take you any further. When it comes to choosing any data analytics course, you should know that there are two different phases of your chosen specialization. The first phase will help in finding out the apt type of analytics training you want, while the second phase would tell you the proper understanding of the practical implications regarding the analytics training. In other words, you need to understand the data analytics jobs and check the perspective of the same, which will further define your training.
The right approach
 After you have the answer for the question, what is data analytics?, the next common question that is posed by most of the people include, what kind of analytics training will be appropriate for me as per the educational background?
This will be your starting phase when it comes to choosing a Big Data data analytics course. However, a majority of people end up failing to find the right training institute since they tend to follow the modern trends. One can see many courses and degrees dealing with data analytics; however, your choice should not be based as per the nice ads or marketing gimmicks but finding out the answer of the question, what do I need to get success in this field and get the data analyst jobs.
The 1st Phase – Choosing the best Data Analytics Course that you require! 
First things first, have your analytics aptitude assessment test. This assessment test may not be a fun thing, but if you are really keen on pursuing your career in this field, then you should have some basic aptitude for data. Once you are clear on this part, you are then supposed to find answers to the following questions and then think of joining any data analytics course:
Are you sure about why you really need this course?
Your perfection should be apparent when it comes to choosing any training on data analytics. This will help you in choosing the right program and course content. So, depending upon the requirements of your chosen domain or data analyst jobs, you should select the course. In other words, you should be crystal clear about what you want from your course.

Check the skills where you lag behind 
You know better about your strengths and weakness. This will eventually help in getting the insight about the kind of skills that you need for your career path. The data analytics jobs would need good technical skill sets along with a good understanding of mathematics for being competent in your work. The popular analytical skills required for the job including the following:
• Good exposure and experience with Data-to-Decision Framework
• The Basic knowledge of business and data analytics
• SQL skills
• Learning skills in working with stakeholders
• Good exposure to predictive analytics
• Experience in handling stats and data analysis tools including SAS, Knime, R, to name a few
Besides these, a working professional would need focusing on stat tools, DTD framework, advanced stat methods, collaborations with analysts, etc. So, depending upon the gap you have in your skill sets, you can further choose the apt data analytics course. You have three key options when it comes to choosing any course, which includes the following:
• The master’s program in data analytics
• A short-term semester program
• Enrolling for any professional workshop
The 2nd Phase- The Analytics Career
If you are keen on making a career in data analytics, you should know the fact that these are not the same as the IT industry in terms of requirement, placement and perks. Since the data analytics courses and subjects are not covered under any undergraduate program, hence getting direct placement in campus is not at all possible. Companies advertising data analyst jobs look for candidates having prior experience in this field.
In other words, you should know how to use the data analysis tools then only you will be called for the interview. Hence once you go beyond the question what is data analytics and start pursuing any program make sure you keep on getting some hands-on experience by being an intern in any company or try connecting with people working with real-time data. This will add you credibility.
On your Toes
Data Analytics is constantly growing and with every passing day, there is something experimented and added to it. If you are choosing any data analytics course without any consideration, then you are committing a blunder. Data is becoming complex with every passing day. You can find a good number of data analysis tools being added to the list that help in handling the data with great security. Data is the future currency of any company, hence if you are considering this career just for fun think again. This is because it would be difficult for you to crack any interview for data analyst jobs.
Different domains have different requirements
Every industry is different, and so are the requirements. This goes without saying that the data analyst jobs you need in one domain would be different than that of other domain. The techniques and data analytics tools you one in one could be outdated in the other. You should know this reality before you join any data analytics course. Be very sure about the domain you choose and get an edge over it rather than trying different things at one time.
Wrapping up
Choosing a data analytics course is not less than rocket science provided you do not know anything about it. If you have a fair about understanding about what is data analytics, and its various other aspects, the above tips can help you in choosing the best course.

Is Data Analytics An Interesting Career Field?

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Reading Time: 2 minutes

One of the biggest job sectors of the last few years, data analytics is seen as one of the most lucrative career options today. In the United States, an estimated 2.7 million jobs are predicted to be taken by data science and analytics by 2020. The value that big data analytics can bring companies is being noticed and companies are looking for talented individuals who can unearth patterns, spot opportunities and create valuable insights.

If you’re someone who’s good at coding and looking to make the next jump from a career perspective, then data science could be your calling. Here are a few reasons you should look out for a career in data analytics:

Higher Demand, Less Skill:
India has the highest concentration of data scientists globally, and there is a shortage of skilled data scientists. According to a McKinsey study, the United States will have 190,000 data scientist jobs vacant due to a lack of talent, by 2019. This opens the door for a good data analyst not just to make money, but own the space.

Good data analysts can take complete control of their work without having to worry about interference. As long as you can provide crucial insights which contribute to the company’s business, you’ll find yourself moving up the ladder faster than expected.

Top Priority in Big Companies:
Big data analytics is seen as a top priority in a lot of companies, with a study showing that at least 60% of businesses depend on it to boost their social media marketing ability. Companies vouch by Apache Hadoop and its framework capabilities to provide them data which can be used to improve business.

Analytics is being seen as a massive factor in shaping a lot of decisions taken by companies, with at least 49% believing that it can aid in better decision making. Others feel that apart from key decisions, big data analytics can enable Key Strategic Initiatives among other benefits.

Big Data Is Used Almost Everywhere:
Another great reason to opt for big data or data analytics as a career option is because they are used pretty much everywhere! With the highest adopters of the technology being banking, other sectors which depend on big data include technology, manufacturing, consumer, energy and healthcare among others.

This makes big data an almost bulletproof option because of the wide range of applications it can be used for.

Most Disruptive Technology In The Next Few Years:
Data analytics is also considered as one of the most disruptive technologies to influence the market in the next few years. According to the IDC, the big data analytics sector is touted to grow to up to $200 billion by 2024.

Thus, big data analytics is going to be the future of computing and technology. The sector is seeing massive growth and a lot of demand. The more you’re able to provide insights that can make a difference in this sector, the higher are your chances of getting a lucrative job.
Whether it’s a data analytics course in Bangalore or any other city, Imarticus will be able to provide you with the right kind of training and knowledge with data analytics courses to help your career soar.

The Importance of Big Data Analytics in The Banking and Financial Services Industry

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Reading Time: 2 minutesIn this data-driven world, Data Analytics has become vital in the decision making processes in the Banking and Financial Services Industry. In Investment banking, volume, as well as the velocity of data, has become very important factors. Big Data Analytics comes into the picture in cases like this when the sheer volume and size of the data is beyond the capability of traditional databases to collect.
Today, data analytics practices have made the monitoring and evaluation of vast amounts of client data including personal and security informant data-driven and other financial organizations much simpler.
There are several use cases in which Big Data Analytics has contributed significantly to ensure the effective use of data. This data opens up new and exciting opportunities for customer service that can help defend battlegrounds like payments and open up new service and revenue opportunities.
For example, in October 2106, Lloyds Banking Group had become the first European bank to implement Pindrop’s PhoneprintingTM technology for detecting fraud. Their technology used AI to create an ‘audio fingerprint’ of every call by analyzing over 1300 unique call features – such as location, background noise, number history, and call type – the o highlight unusual activity, and identify potential fraud.
It cracks down on tactics like caller ID spoofing, voice distortion, and social engineering without any need for customers to provide additional information. Subsequently, Lloyds Banking Group went on to win the Gold Award for ‘best risk and fraud management program’ at the European Contact Centre & Customer Service Awards 2017.
Danske Bank uses its in-house start-up, advanced analytics to evaluate customer behavior and determine preferences, as well as to better identify fraud while reducing false positives.
JPMorgan Chase also developed a proprietary Machine Learning algorithm called Contract Intelligence or COiN for analyzing various documentations and extracting important information from them.
Big Data is also used for personalized marketing, which targets customers based on the analysis of their individual buying habits. Here, financial services firms can collect data from customers’ social media profiles to figure out their needs through sentiment analysis and then create a credit risk assessment. This can also help establish an automated, accurate and highly personalized customer support service. Big Data also helps in Human Resources management by implementing incentive optimization, attrition modeling, and salary optimization.
The list of use cases implemented in the workflows of the Banking and Financial sector is growing day by day. The huge increase in the amount of data to be analyzed and acted upon in the Banking and Financial Sector has made it essential to incorporate increase the implementation of Big Data Analytics.
Knowing the importance of data science is crucial in these sectors and should be integrated into all decision-making processes based on actionable insights from customer data. Big Data is the next step in ensuring highly personalized and secure banking and financial services to improve customer satisfaction.

Basics About Topic Modelling As A Data Analytics Technique

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Reading Time: 2 minutesThe Data Science industry has brought about various new avenues into the world of business and internet of things. Here, data analytics as a field, basically deals with extracting ‘information’ from all the obtained data. With rapid digitalization and increasing of the boundaries of the virtual world, the generation and availability of data is on an all-time high. While some of this data might be pre-processed and structured, most of it is just not structured at all. This causes a lot of difficulties when it comes to the part, where relevant and important information is required. That’s where the tools and technologies of the data analytics industry come into play. These are powerful methods, developed by technology and can be used for sifting through the volumes of data and sniffing out, exactly what a professional is looking for. One of the subsets of these technology is the field of text mining, which basically deals with the technique known as Topic Modelling.
This process mainly deals with, identifying topics present in a text object and deriving hidden patterns automatically, thus aiding in the betterment of decision making. This process differs from other run of the mill text mining approaches, which basically deal with regular search techniques or keywords searching techniques based on any random dictionary. A specific bunch of words that is supposed to be found and observed by a professional, is known as “topics”, which usually are present in large clusters of texts. Topic modelling is the unsupervised approach to performing the above mentioned action, with only the machine and no manual help.
Data Science CourseTopics in other words are, “a pattern of co-occuring terms in a corpus, which keeps repeating itself”. For instance

while building a topic model for healthcare, it should be devised in such a way that it results in words like, health, doctor, patient, hospital and other related words. These topic models are very useful when it comes to processes such as, document clustering, organizing large blocks of textual data, feature selection and retrieval of information from unstructured text and so on. What makes this technique so very important is that it can be used in almost any field from print media to marketing and still be relevant and product centric. For example, there are top gun newspaper publishing houses like, The New York Times, who have a team working on perfecting topic models so as to boost their article recommendations for users. There are a lot of advanced HR teams dabbling in this sector by trying to use it to match perfect candidates, with perfect job profiles
These text models are also used in various other applications such as organization of large datasets of emails, customer reviews and user social media profiles. These are some of the reasons why professionals specializing in this technique are gradually becoming sought after. As the demand of companies rises, the amount of people opting to get trained in these techniques also goes up. Imarticus Learning has various industry intensive course offerings for various data analytics tools like Python, which uses this topic modeling technique most extensively.