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Tag: big data courses in India  . big data analytics courses

What is Business Analytics and Why do You Need it For Success?

Posted on by Imarticus Learning

Are you interested in pursuing a business analytics career? Then you have come to the right place. In the following column, we will explain what business analytics is and how it helps businesses grow. You will also find out how you can pursue a career in this field. Read on…

What is Business Analytics?

Business analytics is an interdisciplinary field that uses computer science, statistics, and machine learning (ML) to enhance the decision-making process of an organization. Its goal is to generate valuable insights that help a company make smarter decisions based on data. Business analytics focuses on narrowing down which datasets are valuable and how to use them to enhance productivity, efficiency, and growth.

It analyses data from multiple sources including CRM tools and cloud solutions. Business analytics relies on machine learning algorithms to find insights from the collected data which would be invisible otherwise. The generated insights help the decision-makers of the organization to forecast future results and the outcomes of the various choices available to them.

Business analytics uses descriptive, predictive, diagnostic, and prescriptive analytics. Selecting one from these different forms of analytics depends on the problem and situation.

Benefits of Business Analytics

There are many advantages of using business analytics. And, following are some of the most prominent ones among them:

Measuring progress: By using business analytics, companies can evaluate their current position more accurately. It allows them to consider multiple factors at once and figure out how much progress they have made in a financial year (or longer duration).

It helps them understand the factors that contributed to their progress and plan accordingly.

Predicting outcomes: Business analytics helps a business determine its trajectory, where it is headed, and what it should expect. Companies can find out the probable outcomes of various situations and modify their future strategies accordingly.

business analytics courses in IndiaBusiness analytics also helps them mitigate risk as they can identify and evaluate the risks surrounding them and their various ventures more accurately. A popular application of business analytics is evaluating investments.

Understanding competition: A company must know what its competition is doing and how it is making progress. Business analytics courses help them evaluate their competitors and find out which factors put them in their current position.

Just as a company can predict its own trajectory by using business analytics, it can forecast the trajectory of its competitors as well.

Learn Business Analytics

As you can see, there are many advantages of business analytics. Due to its versatile application and utility, companies in various industries are on the lookout for skilled business analytics professionals. That is why now is the perfect time to start a business analytics career. If you are interested in entering this field as a professional, then you will need to learn business analytics properly.

There are many business analytics courses in India which you can join. Enrolling in well-reputed business analytics courses in India will help you learn business analytics, its various concepts, and skills better, while also getting certified as an expert.

Having a certification will help you showcase your expertise as a business analytics professional and stand out from your peers. Recruiters prefer certified professionals over others as they have the assurance of their skills and knowledge.

In a nutshell, business analytics is a robust skill that helps companies improve their efficiency, productivity, and planning. The demand for business analytics is also rising rapidly. If you want to learn more about how to pursue a career in this field, then you can check out this business analytics course.

Related Article:

https://imarticus.org/the-growing-need-of-data-storytelling-as-salient-analytical-skillbig-d/

5 Simple Facts About Big Data Analytics Courses – Explained

Posted on by Imarticus Learning

Data Science, Machine Learning or the Big Data Analytics Courses whatever one might refer it as, the subject matter has witnessed colossal growth over the last two decades due to the increase in collection of data, improvement in data collection techniques and methods, and a substantial enhancement in the power of computing data. Various data analyst jobs are pooling talent from multiple branches of engineering, computer scientist, statisticians and mathematicians and is increasingly demanding an all-around solution for numerous problems faced by the businesses in managing their data.
As a matter of fact, not a single stream of business, engineering, science etc. has remained far from the reach of data analytics and are employing various data analysis tools on an on-going basis within their respective industries. Perhaps it can be one of the best times for students to enroll in the big data analytics courses and be future ready as the future is in data analytics.
But, as data analytic jobs are deemed to be in an upward trend shortly, here are some simple facts one needs to know about data analytics before embarking a big data analytics course or a career in data analytics. 

  1. No Data is Ever Clean

Theoretically, as taught during a  data analytics course,  analytics in the absence of data is just a group of theories and hypothesis, whereas data aids to test these theories and hypothesis towards finding a suitable context. But, when it comes to the real world, data is never clean and is always in a pile of mess. Organisations with established data science centres to say that their data is not clean. One of the major issues organisations face apart from missing data entries, or incorrect entries is combining multiple datasets into a single logical unit.
The various datasets might face many problems which prevent its integration. Most data storage businesses are designed to be well integrated with the front-end software and the user who generates the data. However, many-a-times, data is created independently, and the data scientist arrives at the scene at a later stage and often ends up being merely a “taker” of data which is not a part of the data design.

  1. Data Science is not entirely The user will need to clean some data manually

A vast majority of people do not wholly understand what data analytics is? One of the most common misconceptions about data analytics is that the various data analysis tools thoroughly clean the data. Whereas, in reality, as the data is not always clean, it requires a certain degree of manual processing to make it usable, which requires intense amount of data processing, which can be very labour intensive and time-consuming, and the fact remains that no data analysis tools can completely clean the data at the push of a button.
Each type of data poses its own unique problem, and data analyst jobs involve getting their hands dirty and manually processing data to test models, validate it against domain experts and business sense etc.

  1. Big Data is merely a tool

There is quite a lot of hype around the Big Data, but many people do not realize that it is only a collection of data analysis tools which aids working with a massive volume of data promptly. Even while using Big Data, one requires the utilise best data modelling practices and requires a trained eye of an expert analyst.

  1. Nobody cares how you did something

Executives and decision making are often the consumers of various models of data science and continuously require a useful and a workable model. While a person performing one of many data analyst jobs might be tempted to provide an explanation to how data was derived, in reality, these executives and decision makers care less how the data was acquired, and are more interested in its authenticity and how can it be used to improve any of their business functions.

  1. Presentation is Everything

As most of the consumers of analytic solutions are not mathematicians and are experts in their respective fields, presentation plays a vital role in explaining your findings, in a non-technical manner, which is understandable to the end user. A PowerPoint presentation loaded with infographics can aid a data scientist in conveying the end-user their message in a language and mode of communication with is easy of them to understand.