What is The Best Way to Jump Into Data Analytics Within The Finance Industry?

Mayanka Chowkar talks about getting placed at a leading Data Analytics finance firm after her Imarticus stint.

I completed my B.Com, and M.Com as well, and was on the lookout for a platform to jump into the finance industry.

I felt Imarticus would be a great way to get into the industry.

Some of my friends have done this Big Data Analytics Training course already and landed good placements. Seeing that, I thought it would be an excellent opportunity for me to also get into the industry through this course and through Imarticus.

I’d rate my experience with Imarticus as a solid 4. I loved most of the concepts and information that are given during the course. The faculty is also excellent.

The Imarticus Learning placement system worked wonders for me.

The staff members and faculty on the course and in Imarticus, in general, have helped me by giving me placement opportunities even before the course ended! By doing this course, I got a once-in-a-lifetime opportunity to learn about the industry and was placed in a good company, too. I’m really excited and happy about this.

I have been placed as an associate and have been tasked with handling the derivative operations. I will be joining my new workplace soon, and I’m so excited about it, I don’t have words to express enough!

Want to learn in-demand skills in the data analytics industry? Talk to an Imarticus counselor today.

Learning Vs. Training & Development!

Have you ever wondered how learning is different from training? We often encounter such trivial questions with no prominent answer to address the question. From a broader perspective, those two seem interchangeable; hard to point out the difference but when we dive deeper into the subject, we will observe that we are dealing with two different things and how they complement each other.

Let’s delve into the details of the same.   

The Process Of Learning 

At the very core of the learning process resides the desire of a person to gather knowledge about any given agenda or topic. The internal inquisitiveness drives the learning zeal rather than an external force or command. The innate quest to know more about a particular stream, agenda, phenomenon, etc. fuels the learning process. The process of learning entails the absorption and retention of information with context. It could be to achieve a particular goal or just to quench the knowledge thirst.

Learning is more about the whole experience of boosting your knowledge, which later will be applied to unknown and unforeseen circumstances. Learning results in enhanced skills and increased knowledge. Since learning is about absorbing important information, the way the knowledge is imparted has a lot of impact on how efficiently the learning takes place. In short, it is linked to the process of training, how well you are trained influences, how well you learn.

The Process Of Training & Development

What comes to your mind when you hear the word training and development? Well, the first thought is that of a strict curriculum and an instructor to facilitate the same. The process of training involves communicating relevant information and knowledge through the means of speech, written manuals, presentations and other such techniques in a manner that instructs the trainee and helps fulfill the objective.  Training is more process-oriented and focuses on skill up-gradation using contextual knowledge sharing.

Corporations use training methods to boost productivity by focusing on delivering important information regarding job roles. After joining a corporation, every new employee goes through a rigorous training process that helps them to be aware of their organization, objectives, day-to-day operations, departmental functioning, tools required to do the job, etc. The end goal is to teach the individual how to perform their job and the process they need to follow for optimum results. The process of training and development is more goals oriented.

Comparing the two

Now that we have established what both the processes are, let us compare and find out how they differ from each other. At the center of our discussion is the force of motivation that differentiates both the processes. When we talk about learning it is propelled by the inner motivation of the individual rather than the force of an external curriculum.

Training and development, on the other hand, are external forces that guide the process of learning a particular skill through a robust curriculum and discipline with an end goal of personal skill development. The process of learning is more knowledge-oriented whereas the process of training is more skill-oriented.

Training is mostly used by corporations to impart individuals with skills that will help to do the job or complete the objective. Learning, on the other hand, is the absorption of information that can be used in multiple contexts and scenarios based on individual understanding.

The process of training and development has a standard way of imparting relevant knowledge whereas the process of learning is subjective and depends upon the individual capacity to absorb and retain information. Even if a group of individuals is trained using the same instructor and information their learning curve might be different depending on their strengths and weaknesses.

How Big Data is Implemented in Business?

Big data is everywhere, and behind every organized solution, you face on the daily. The term refers to massive sets of data that inundate businesses during day-to-day operations– but it’s not the data dump itself that matters to businesses, but the goldmine of insights it reveals once it’s sifted through, analyzed and put into plain and simple words.

The amount of data an average business sees in a day is torrential. Big data scientists find themselves having to deal with the ‘three V’s’ as they’re called:

  • Volume: tonnes of data from a dozen different sources including social media and daily transactions
  • Variety: structured and unstructured data; numeric or stock; video or audio
  • Velocity: Breakneck speeds at which data flows in from all channels into the dump

Big data is highly complex and interrelated, which means sifting through and making sense of it can be quite the herculean task. However, the insights gathered through the process of going through the dump can enable reductions in costs, effort and time. It can also open up new revenue streams, enable the development of new products and bolster analytical and strategic business decision-making.

How is big data implemented in business?

The traditional method of storing data is by using relational database software, built for Structured Query Language (SQL). However, the future of big data began looking too complex for businesses to be able to control, which led to the introduction of NoSQL.

NoSQL is customizable and scalable, making them ideal solutions for businesses both big and small. It’s made specifically for big data, and stores data in the following ways:

  • Document storage
  • Graph storage
  • Key-value storage
  • Column family storage

NoSQL provides real-time, super-quick access to data, without the need for schemas and columns. This allows the running of real-time programs towards furthering business processes. Without the schema middleman, data scientists can directly interact with tonnes of data, which in turn saves any business a lot of effort, time and money.

Why is big data important in business?

Industry professionals and students alike are looking to learn big data analytics and science because of the plethora of job options it opens up in the world of business.

Access to information

Bug data opens up new avenues for businesses to explore, be it in terms of generating revenue, introducing new products or strengthening marketing. It enables real-time data monitoring and allows for A/B testing where necessary without too much of an impact on ‘business as usual’ if the strategy doesn’t work out.

Faster decision-making

Hadoop and other in-memory analytics software allow businesses to conduct analyses on information immediately, further enabling them to come to crucial decisions faster and based on data instead of speculation. Big data can also be leveraged to lookup more updated and dynamic data, allowing decision-making to be accurate as well.

Conclusion
As a good data analytics course will show you, big data is in use across several burgeoning industries, each with their own means and end goals. Be it manufacturing, pharmaceuticals, retail or even governments, there is no place big data can’t be implemented– which means there is no place big data specialists can’t go.