Contact Us
×

Author: Imarticus Learning

How To Advance Your Business With Analytics & Build The Right Team?

Posted on by Imarticus Learning

In 2020, data is a goldmine of information, and if you can collect and analyze the right data sets, a lot can be achieved in a short period of time.

As companies around the world, start recognizing and collecting more data points from their customers, it is crucial than ever before to have a data analytics team, which can not only process and analyze the collected data but also emphasize sharing key insights which will assist you in advancing your business.

LinkedIn, the number one job search portal reported that 2020 saw a 25% increase in professionals who are seeking a Big Data Career in data science and analytics.

Bi Data CareerWhile this clearly indicates that the importance of data scientists is on a steady rise, it also indicates that companies need to better analyze the capabilities of each individual domain to choose the right man for the job.

How to Choose and Build the Right Data Analytics Team for Your Company?

One of the first and most crucial aspects to understand and embrace is the fact that in 2020, data scientists come with a variety of different skill sets, and thus it is essential to recognize each of the skills and categorize them into the functions best suited for.

While building an analytics team for your organization, you can follow either of two different approaches.

  1. The Direct Method of Segmentation
  2. The Indirect Method of Appreciation

The Direct Method of Segmentation

The concept of the direct method of segmentation is based on the ideology that each data scientist depending on their skill set can be grouped into either of three different designations and then hires can be made based on deciding which skill is required first.

  1. Data Engineers: Data Engineers are the crux of any data analytics team you want to design. The main skill sets you should look for in a data engineer include, ETL (Extraction, Transformation, and Load), Data Warehousing, data processing, and other similar roles.The fundamental job of a data engineer can be summarized as preparing the data for further analysis by data scientists and analysts, who form the rest of the team. They generally have a degree in Big Data Analytics Training.

    Big Data Career

  2. Data Analysts: Using the data prepared by data engineers, analysts extract critical information and decisions which are helpful in solving problems and contribute to advancing business decisions within the organization.
  3. Data Scientists: Data scientists form the last hierarchy of the team and are mainly responsible for crafting and perfecting algorithms using either Machine Learning or Artificial Intelligence to make compelling decisions from unstructured data sets. While a data scientist can easily be tasked with the responsibilities of both analysts and engineers, in big teams these designations are separated for better utilization of time and resources.

The Indirect Method of Appreciation

The indirect method of appreciation is based on the concept of recognizing people who have a broad range of skills, but also in-depth knowledge in a few key areas. This method of hiring can be understood using the “T-Shaped” skill concept, where the horizontal bar of the T represents the broader knowledge set of the hires, and the vertical bar represents the specialized knowledge in key areas.

The overall aim of this methodology is always to find the right set of people, who have the expertise and the knowledge to get the work done in a timely manner.

Conclusion

Building the right data analytics team for your business can not only contribute to its immediate success but also long-term growth. Thus always make it a point to invest the right amount of resources and figuring out which methodology of hiring works best for your business.

The 5 Most In-Demand Skills In The FinTech Industry!

Posted on by Imarticus Learning

If there is one field that is growing at a rapid pace and which also has a lot of scope for students in India, it is fintech. Short for financial technology, it has revolutionized the way we manage our finances in a short span. Whether it is small-scale investments or corporate finance, fintech has managed to provide better solutions like mobile banking, wallets, UPI, and other IT-driven financial services.

This is the same reason why a fintech career is one of the most sought-after paths for aspiring students today. But with that aspiration comes the question of specialization. What skills to master? And what fintech courses to take?

Fintech online certification course in IndiaHere’s help in the form of a starter guide about the 5 most in-demand skills in the industry.

1.      Strong Understanding of Programming Languages

Knowing the basics of coding and having a working knowledge of at least one major programming language is essential to even enter the world of fintech.

And when you do enter, just knowing a language is not enough. A fintech career requires you to innovate in that language and come up with solutions to modern problems. This is only possible if you know the language (or languages) inside out.

Fintech certification courseSome of the most common languages used in fintech are JavaScript, Python, and SQL. You can learn more about them through easily available fintech courses online.

2.      Mathematical and Analytical Skills

You have to be very sharp with numbers.

Some people have a natural way with numbers and that is expected in any student who wants to make it big in the fintech industry. In addition to accountancy and bookkeeping skills, you also need to be strong with charts and graphs and mathematical analysis. Tech tools involved in fintech are extremely useful and knowing how to use them even more critical.

3.      Blockchain Skills

An intermediate-level expert in blockchain has a better chance of nailing a fintech job interview than a financial expert. Why?

Because fintech companies are looking for talent who have a bend with technology. Since blockchain is considered the next big thing in online security and privacy, experts in the subject are in demand.

This makes blockchain a hot skill and something that you should study on the side as you prepare for your fintech career.

4.      Cybersecurity Skills

Another in-demand skill for your fintech career is related to cybersecurity. This is obvious because security is one of the most crucial aspects of fintech. A company creates a mobile wallet app, and one of the most important things it needs to ensure is the safety of its users’ private information.

With the constant threat from hackers looming, companies need to make sure that their products are secured with top-notch technology. This is where your cybersecurity skills come into play.

Knowing existing security standards such as the FIDO alliance, two-step verification, strong authentication, and other related concepts then becomes paramount.

5.      Machine Learning and Deep Learning

Last on the list is machine learning, which is one of the most in-demand tech skills in general. The world is still trying to make communication between computers and humans free-flowing, and having one more expert getting involved in it is a welcome move.

If you are a finance student, it would be good to expose yourself to such tech concepts as you try to build a fintech career in India.

The recent change in the high school education framework of India further makes fintech an appealing path. This is because students can now take two more years to decide on their interests and start focusing on specific employable skills from early on. Start now and enroll in a fintech course today.

Optimisation In Data Science Using Multiprocessing and Multithreading!

Posted on by Imarticus Learning

Every day, there is a large chunk of data produced, transferred, stored, and processed. Data science programmers have to work on a huge amount of data sets.

This comes as a challenge for professionals in the data science career. To deal with this, these programmers need algorithm speed-enhancing techniques. There are various ways to increase the speed of the algorithm. Parallelisation is one such technique that distributes the data across different CPUs to ease the burden and boost the speed.

Python optimises this whole process through its two built-in libraries. These are known as Multiprocessing and Multithreading.

Multiprocessing – Multiprocessing, as the name suggests, is a system that has more than two processors. These CPUs help increase computational speed. Each of these CPUs is separate and works in parallel, meaning they do not share resources and memories.

Multithreading – The multithreading technique is made up of threads. These threads are multiple code segments of a single process. These threads run in sequence with context to the process. In multithreading, the memory is shared between the different CPU cores.

Key differences between Multiprocessing and Multithreading

  1. Multiprocessing is about using multiple processors, while multithreading is about using multiple code segments to solve the problem.
  2. Multiprocessing increases the computational speed of the system while multithreading produces computing threads.
  3. Multiprocessing is slow and specific to available resources while multithreading makes the uses the resources and time economically.
  4. Multiprocessing makes the system reliable while multithreading runs thread parallelly.
  5. Multiprocessing depends on the pickling of objects to send to other processes, while multithreading does not use the pickling technique.

Advantages of Multiprocessing

  1. It gets a large amount of work done in less time.
  2. It uses the power of multiple CPU cores.
  3. It helps remove GIL limitations.
  4. Its code is pretty direct and clear.
  5. It saves money compared to a single-processor system.
  6. It produces high-speed results while processing a huge volume of data.
  7. It avoids synchronisation when memory is not shared.

Advantages of Multithreading

  1. It provides easy access to the memory state of a different context.
  2. Its threads share the same address.
  3. It has a low cost of communication.
  4. It helps make responsive UIs.
  5. It is faster than multiprocessing for task initiation and switching.
  6. It takes less time to create another thread in the same process.
  7. Its threads have low memory footprints and are lightweight.

Optimisation in Data Science

Using the Python program with a traditional approach can consume a lot of time to solve a problem. Multiprocessing and multithreading techniques optimise the process by reducing the training time of big data sets. In a data science course, you can do a practical experiment with the normal approach as well as with the multiprocessing and multithreading approach.

Data Science Courses with placement in India

The difference between these techniques can be calculated by running a simple task in Python. For instance, if a task takes 18.01 secs using the traditional approach in Python, the computational time reduces to 10.04 secs using the pool technique. The multithreading process can reduce the time taken to mere 0.013 secs. Both multiprocessing and multithreading have great computational speed.

The parallelism techniques have a lot of benefits as they address the problems efficiently within very little time. This makes them way more important than the usual traditional solutions. The trend of multiprocessing and multithreading is rising. And keeping in mind the advantages they come up with, it looks like they will continue to remain popular in the data science field for a long time.

Related Article:

https://imarticus.org/what-is-the-difference-between-data-science-and-data-analytics-blog/

What does Intrusion in IT mean? And How can it be Detected?

Posted on by Imarticus Learning

Network security, for any organisation, is of prime importance. This does not mean protecting the network with the use of firewalls, but it goes deeper than that to pick up potential threat factors without replacing the traditional or primary security efforts like the encryptions or authentication methods.

To understand this better, it is important to first discuss what intrusion in IT means. Intrusion in IT, to simply put it, it is when a hacker wants to make way in your network with malicious intent. This can be detected by a Network Intrusion Detection System. Why are we using the term network here?

Because an intrusion detection system keeps a check on packets of a network wire, with the main objective of keeping away the hacker from entering or breaking into your system, it does so by analysing the movement on your network, to evaluate any anomaly or signs of threat.

Let us understand the main Objective and Functions of an Intrusion Detection System

  1. To Detect Attacks on the network – by providing real-time monitoring with an intrusion detection system can detect any potential threats or attacks as and when they occur.
  1. Provide Information on the attack – the intrusion detection system is equipped to provide information on an attack if it detects one.
  1. Provide Resolution – in an event, an attack was detected, it not only provides information of the attack but goes forward and applies corrective actions to manage the threat or an attack.
  1. Historical Data – the system stores the information on events locally and also when a case of attack is registered.

A network detection system is most strategically placed on points in a network so that it can monitor the traffic travelling to or from different devices on that network. There are mainly two types of network Intrusion detection systems, one should understand the applicability of this to decide on which one to apply.

Signature-based intrusion detection system, which is programmed towards identifying a specific type of vulnerability. Hence this system will not report every anomaly but only specific ones, thus reducing the number of False Positives.

Anomaly-based intrusion detection system searches every attack that is not meeting with the norms, hence in this system, the rate of false positives is very high.

Many companies set a large network identification system as a backbone network, which monitors blanket traffic on the network, others set up small systems to monitor traffic for a particular server, switch, gateway or router.
Besides monitoring traffic, an intrusion detection system can also scan system files looking for unauthorized activity and maintain data and file integrity.

The intrusion detection system can also work for a proactive role instead of a reactive role. It is proactive as it’s possible uses involve scanning firewalls for potential exploitation and scanning live traffic to see what is actually emerging.
A point to note is that the intrusion detection system is not a replacement for firewalls or any primary security systems, which are put in place to mitigate risks. This system is a backup network integrity device. And either one of the systems cannot replace another.

Imarticus offers an extensive certification course in Business Analytics for freshers and working professionals to understand the depth of IT Intrusion :

Data Science Prodegree: This program is co-created with Genpact as Knowledge Partner. This program helps you with the deep understanding of Data Analysis and Statistics, along with business perspectives and cutting-edge practices using SAS, R, Python, Hive, Spark and Tableau.

Post Graduate Program in Data Analytics: This program helps you to understand foundational concepts and hands-on learning of leading analytical tools, such as SAS, R, Python, Hive, Spark and Tableau as well as functional analytics across many domains.

To know more, please refer to our website: Data Analytics Course
To learn more about the Analytics watch this space until next week for the big news!

The Rise of The Indian PE Market A Deep Dive into The Indian Private Equity Market

Posted on by Imarticus Learning

With fifty percent of the 1.1billion population being youngsters, India was a primary target for private-equity firms and their investors in the early years of the century. Private investors poured around 93 billion dollars into India in this period. After a healthy return of 25% gross returns at the exit, yields fell sharply to 7% returns at the exit between 2006 and 2009. This fall caused Indian PE market to lay low for a while. But if you check, in 2017 with a $26 billion investment and over 60% growth, the private equity market of India is showing a stronger comeback.

Reasons for growth

If we look into the reasons for the recent growth of the PE market in India, improvement in economic indicators, the formalized economy and the government handling NPA issues are plausibly the biggest of many. Despite the early setback, the investors are now coming back to India as a sustainable destination. It has resulted in a 48% growth of India-focused fundraising.

The diversification of fund sources is also a significant reason for this growth. The non-performing asset in the forms of sovereign wealth funds and pension funds started to participate and accounted for one-fifth of total investment. The registered alternative investment funds (AIF) accounted for more than $5 billion. There was also a considerable increase in the number of active players in the market and the number of institutional investors.
Combined, all these factors propelled private equity fundings to a new benchmark.

Competition in Market

The PE market in India witnessed a steep growth in competition for deals in 2017. Increase in the number of participating funds and PE funds developing pockets of strengths across sectors resulted in the competition like never before. The top 15 deals contributed about 50 percent of total investment. A whopping 95% growth has been registered in the size of sales greater than $10 million.

Exits…

we witnessed more than 200 exits taking place in the last year primarily driven by the transaction value than an increase in deal volume. With a 7% increase in the number of exits, there was a 60% increase in exit value. The exit value reached a total of $15.7 billion.
Considering India’s economic conditions we can expect more exits to happen shortly. Most funds are awaiting moderation in valuation to decline by 2 to 4 percent in the next five years.

Future of PE in India

Making new deals are going to be the top priority for funds in the following year. Since more funds are starting to engage in the market, we should expect more co-investment opportunities to limited partners. This can lead to reduced risks thus ensure more investment from limited partners.
A critical challenge in the Indian market is found to be the mismatch in valuation expectations between investors and firm owner. The leadership issues at portfolio companies are another common issue you would face if you are to go in the market.

Beginners Guide to Investment Banking

Posted on by Imarticus Learning

Investment banking is an expansive and challenging field which several individuals can pursue. Here is everything you need to know to kickstart your career in investment banking.

Investment banking is a field that one can pursue with passion and determination. It is that division of a bank or a financial institution that helps companies secure, implement and manage their finances well in order to succeed and grow. It is a highly dynamic and volatile field which is looking for individuals who have not only completed an investment banking course but are also charismatic and driven.

There are various functions and areas that one gets to operate in, upon completing an investment banking training from evaluating assets to auditing to securing funds and client relationship management. Investment bankers are talented and do multi-functional roles in their companies. While specialization exists, At the heart of investment banking is the ability of the bank to raise funds for the clients and this is done predominantly by issuing debt or selling equity of a company.

Investment bankers need a good quality radar in order to determine the best possible way to raise money quickly. These are crucial decisions which will determine the future of the company and hence investment bankers are highly paid. This also means the job entails long hours and strategic thinking at every step of the way.

Here are the top things that beginners get to do in the field of investment banking.

  • Raising capital: One of the top job functions that every investment banker does is the ability to raise money for a business. Every company needs an understanding of how to raise finances to run the business and to take off. Raising capital will then create enough to buy equipment, employ people and create products and sell. Therefore, an important area of expertise for those pursuing a career in investment banking is knowing how to raise funds for a company.
  • Assisting in Mergers & Acquisitions: Another important aspect of an investment banker’s role in banking is to help clients evaluate other companies before acquiring them. This means taking stock of the assets and liabilities of the other company, auditing and evaluating and creating a forecast which can benefit the client.
  • Issuing Debt: A primary function of an investment banker is to issue bonds to the right investors. This will help raise the required capital for their clients. Companies also hire investment bankers when they must go public i.e. issue an Initial Public Offering (IPO) to raise funds.  The success of this plays a crucial role in how the company flourishes in the future. Since aggressive sales skills are required for this, it is a highly competitive field which is rich in rewards.

Conclusion
Investment banking begins to be lucrative and continues to climb the growth trajectory provided one is hardworking, dedicated and sharp. It is a great career for those interested in finance.

Also Read: How Good is Investment Banking as a Career

Everything you Should Know About Business Analytics!

Posted on by Imarticus Learning

Business analysts (BAs) are responsible for bridging any issues in the IT department and the business by creating new models after running strategy analysis. They evaluate processes, decide the needs of an organization and provide suggestions supported by appropriate data and draw reports to executives and stakeholders. 

BAs work with business leaders and users to see how data-driven changes to processes, products, services, software, and hardware can improve efficiencies and add esteem. They must articulate related thoughts or share observations yet in addition balance them against what is technologically practical and financially and functionally sensible.

How to make a career in business analytics?

Possession of hard and soft skills is an important prerequisite for becoming a business analyst. Not all business analysts need a background in IT as long as they have an overall understanding of how systems, products, and tools work.

On the other hand, some business analysts have a solid IT background and less experience in business but are keen on moving away from IT to this hybrid job. 

A relevant bachelor’s degree in business administration or finance will provide the necessary footing for your career as a BA, as any of the subjects hones your logical skill set and gives you a comprehensive layout of how businesses operate and meet targets. 

Numerous companies additionally incline toward individuals with an IT and engineering background. This is on the grounds that business analytics is highly dependent on software and technology. 

At the postgraduate level, you can choose to get straight to business analytics by opting for a certification course in Business Analytics. 

Business Analytics CourseIn any case, for some higher corporate positions like becoming a member of the board or working on high advisory positions, companies lean toward employees with an MBA (Master in Business Administration). This degree won’t throw you straight up into business analytics, but it can kick-start your career and fetch you a good salary. 

Further, a business analytics certification course with placement opportunities can extend employment opportunities, enhance pertinent skills and offer a higher return on investment in a limited timespan.

Notably, candidates with a business analytics certification are in high demand by the companies hoping to employ a BA resource. And, this interest area is considered by top colleges which have begun to offer business analyst courses online that are broadly acclaimed and perceived by the best organizations around the world.

Some of the business analysis certification courses with placement opportunities that strengthen the foundation of aspiring BAs are:

  • Certification for Business Analysts
  • Business Analyst Certification for Beginners
  • Certification of Competency in Business Analysis
  • Certified Agile Business Analyst Certification
  • Agile Analysis Certification Training
  • PMI Professional in Business Analysis

To have the high ground in altered business systems, possessing a business analytics certification is an absolute necessity for anybody seeking a vocation in analytics. In this day and age, it is self-perceived that data is a basic requirement in any calling.

In the business and sales industry, past data is utilized for decision-making and the development of business. Now you know how important a BA is, so why wait? Enroll in a Business Analytics Online Course to gain business analytics certification and grow your career.

 

Related Article:

https://imarticus.org/why-working-professionals-must-learn-business-analytics/

Everything You Need To Know About Forensic Accounting!

Posted on by Imarticus Learning

Forensic Accounting refers to the application of financial skills to resolve disputes of fraud and misconduct of finances in business finances. It is an integration of accounting, investigation, and auditing with a sound knowledge of business and legal systems. The scope of Forensic Accounting includes:

  1. Designing an accounting process for the verification of data.
  2. Looking for an unusual development in accounts for any possible fraud.
  3. Continuous surveillance of transactions of a variety of businesses.
  4. Performing a routine schedule of audit processing.

Need for Forensic Accounting

These days, almost no domain is left untouched by fraud, dishonesty, corruption, money laundering, etc. Forensic Accounting is a field that checks all these activities.

Criminal Investigation: Forensic Accountants prepare detailed reports of financial implications in case of fraud. It helps the police and the investigating authorities in examining the case in detail.
Financial Analysis course with placement in Iindia
Dispute Settlement: Forensic Accounting professionals help resolve disputes in business communities. They settle intellectual property infringements, liability claims, etc.

Professional Negligence: In the case of employee negligence leading to non-compliance with auditing and accounting standards, Forensic Accountants examine the loss through quantification.

Detection of Fraud: Forensic Accountants detect fraud by tracing the papers and other activities of the employees of the company. They tactfully devise strategies to find out the truth.

Forensic Accountants – Skills and Qualifications

Forensic Accountants are very important professionals for every organisation. From public to private, every entity needs to ensure that they comply with the governance codes and establishes transparency in its systems. Forensic Accountants help in this cause by maintaining fair accounting and detecting any misconduct.

Due to the nature of their tasks, Forensic Accountants can find employment in Banks, Multinational corporations, Police forces, Freelance, Insurance companies, and even government agencies, etc.

To be a Forensic Accountant, one needs to do a bachelor’s or master’s degree in Accountancy. A diploma in banking and finance can also provide the necessary qualification required to build a substantial career in this field.

Financial Analysis course with placement in IndiaCommerce graduates can also pursue a career in Forensic Accounting with a financial accounting course.

A Chartered Accountant with experience in accounting and auditing also makes for an eligible candidate for a Forensic Accountant.

To become successful in the Finance career, one should first work under an expert Forensic Accountant as it will provide them with insights about this career. The necessary skills required for the role of Forensic Accountant are:

  • Analytical aptitude
  • Attention to details
  • Communication skills
  • Persistence
  • A knack for finding loopholes
  • Compliance with the ethical code of conduct, etc.

Forensic Accounting in India

As India is a country where monetary frauds and scams are common in business organisations, the RBI has made Forensic Accounting audits mandatory for all banks. A Serious Fraud Investigation Office (SFIO) has been established, which has boosted the growth of this sector and enhanced job opportunities. With the growing online fraud and cybersecurity breaches, the demand for Forensic Accounting professionals is increasing.

The income in this field is also quite lucrative. The average salary of Forensic Accounting professionals is around INR 984,533 according to payscale.com.

One can find jobs in this sector through related titles like Fraud Analyst, Risk Analyst, Fraud Investigator, Anti-Money Laundering Analyst, apart from the usual Forensic Accountant title. The salary incentives grow with the number of years of experience in this field.

Conclusion

Given the present scenario of financial irregularities in the country, Forensic Accounting has a very bright future. Also, the lack of qualified and experienced Forensic Accountants in India makes this a very valuable career for students to pursue.

Related Article:

https://imarticus.org/what-is-a-financial-analyst-course/

What is The Language Used To Make Artificial Intelligence Programs?

Posted on by Imarticus Learning

A.I. or Artificial Intelligence is considered to be the next big thing in the science community. Many people are worried about its lousy use; many have raised the fear of Skynet in the actual world through the artificial intelligence programs. Well, dangerous or not, when it comes to being in the league of new technology, big MNCs don’t like to fall back.

Having said that it is clear that people who have done big data and machine learning courses are the ones who are getting selected in big MNCs. While learning these courses, the main question that arises is: in which programming language are these Artificial Intelligence programs written? The answer is more than one. Let us list out the big guns of the artificial intelligence industries –

  • Python: Since its discovery, Python has gained significance as a popular programming language. Many artificial intelligence programs are written in this programming language. Python is liked among the personnel working in the artificial intelligence field due to its syntax simplicity and versatility. It is easier to learn than C, C++, Java, etc. It is more dynamic and supports neural networks, which makes it easier to develop NLP solutions in an ideal structure.
  • C++: C++ may be a little bit complex than Python, but it is one of the fastest programming languages out there. As artificial intelligence programs are vast numbers of lines of codes, the fast processing speed of C++ gives it an edge over the others. C++ allows the use of humongous algorithms while presenting statistical data. C++ is considered to one of the most suitable programming languages to learn for writing artificial intelligence programs.Investment Banking
  • Java: Java is popular among the programmers because of its ability to be a multi-paradigm programming language. The two main principles followed by Java are object-oriented programming and WORA principle. WORA or Written Once Read/Run Anywhere makes it possible to run Java programs over any system without recompiling it. It is best suited for Neural network and heavy-weight artificial intelligence programs.
  • LISP: LISP is not only a single programming language, but it is a family of programming language. It belongs to the category of the oldest programming languages in the market after FORTRAN. Although old LISP has evolved as the time passed to become one of the most influential programming languages used in artificial intelligence programs, it is favored0 in the account of the freedom it offers to the developers. LISP possesses an exceptional macro system which eases the work of implementation and investigation of specific intellectual intelligence programs.
  • PROLOG: PROLOG is the next oldest programming language in this list. It earned this position due to its underlying mechanisms which come in handy for various artificial intelligence programs. For example, PROLOG’s basic mechanisms include pattern matching, tree-based data structuring, automatic backtracking which are crucial for artificial intelligence programs.
  • Its mechanisms enable a flexible framework which is liked by the programmers. It is also known as a rule-based declarative programming language as its processing is done based on specific rules and elements which lay the very ground of artificial intelligence programs. PROLOG is one of the primary programming languages for artificial intelligence programs. It is used in some artificial intelligence enabled medical systems also.

So these were the first programming languages used in the industry to write artificial intelligence programs. These languages can be learned from various big data and machine learning courses. Organizations like Imarticus Learning are doing an excellent job in equipping people with the knowledge of these programming languages by their A-listed courses.

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

Posted on by Imarticus Learning

 

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.

Get a free 1:1 Imarticus counselling
Get a free 1:1 Imarticus counselling