Big Data – N. L. Dalmia Institute of Management

What to expect after a PGDM in Business Analytics?

October 20, 2022
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| Big Data, Career, PGDM
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Data is the new oil. Oil, only when refined, can create products of value such as chemicals, natural gas, etc. Similarly, data must be cleansed, transformed, and analysed to derive value. If you are wondering what ‘value’ is, that’s exactly what a business analytics course will uncover. It can help you to understand the process of analysing data generated during business operations. If a company can leverage this data to make well-informed strategic decisions, the probability of the decisions being correct is very high. Such decisions, which are rich in data-driven insights, can create a meaningful impact on a company’s top line and bottom line.

A Post Graduate Diploma (PGDM) in Business Analytics will enable you to play a key role in transforming the data generated across the various departments of the company into rich insights. It is probably the only role wherein even at the junior-most level in a company, your work will significantly impact its overall growth and help to accelerate its business prospects.

Here’s a list of career opportunities that can be pursued post a PGDM in Business Analytics:

1. Data Scientist: Data can be classified as ‘structured’ data (which is in rows, columns, and tables) and ‘unstructured’ data that could come from email, audio files, videos, social media posts, call center data etc. As a huge proportion of the relevant data across an organization is ‘unstructured’, it is critical to analyze its impact on business and getting an org-level view of its impact as against analyzing data in departmental siloes. That’s exactly where a data scientist comes in. With his expertise in data, mathematical models, statistics, etc., a data scientist can sieve useful insights from humongous volumes of

data. Companies across the world are extensively seeking talented data scientists. A PGDM in business analytics will help you to become a preferred choice of companies that are looking for data scientists and analysts.

2. Analysts across key functions: The scope of a PGDM in Business analytics is wide ranging. It is because the course teaches various aspects of business including operations, finance, marketing etc. and empowers you with the capabilities to transform the data generated from daily operations across these departments into rich business insights. For instance, a person with a PGDM in business analytics is equipped to help a company to streamline its supply chain, ensure optimum economic order quantity to reduce wastage, and enable the company to have ‘Just in Time’ inventory across its point of sale to keep losses to the minimum. Similarly, they can work on various models and share insights that can sharpen marketing campaigns, enhance customer lifetime value (CLTV), and help to onboard more customers by curating offers as per demographic data and buying pattern-based insights.

3. Chief Data Architect: Before attaining a PGDM in Business Analytics, you might have graduated in technology and may have relevant work experience. If so, a PGDM in Business Analytics can add a new dimension to your career prospects. We live in an age of digital/ mobile-first startups that champion the cause of ‘convenience’ that we so dearly love. Such apps that help you get everything at your doorsteps with just a click (literally), need very robust data frameworks and models to enable real-time decision-making with respect to prices, routes of delivery, bundled offerings etc. To manage these aspects seamlessly, companies hire data architects who are the custodians of the organizations’ technology infrastructure that

powers or holds the data. Their technical understanding, knowledge of domains and functions, and ability to liberate data from traditional siloes is invaluable. They can build the required architecture and frameworks to derive rich insights from the data that can be viewed by strategic leaders of the business, not in isolation but in sync with various other parameters to gauge organizational level impact. Hence, a chief data architect is pivotal in creating a digitally transformed data- powered business.

Data and Business Analytics is a very nascent field and companies are still discovering the true potential of the data that they have. This includes the current data that they generate and the data that they must have archived. The scope of a PGDM in Business Analytics will further amplify as companies start discovering means of creating ‘impact’ with the data that they generate. Hence, a PGDM in Business Analytics is not only a course for today’s times but also for the future. It will stay highly relevant in the times to come. Hence, a PGDM in Business Analytics will open a plethora of opportunities across sectors, domains, and geographies for a student. What more can one ask for?

Here’s What You Can Expect from Top Management Institutes in Mumbai

March 24, 2021
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| Admission Consultation, Big Data, Career, MBA, MBA Advice
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Nowadays, marketing professionals are trendy among multinational companies, looking for aspiring talent with management degrees and expertise. With that said, a lot of people are encouraged to gain an MBA in marketing from a renowned university.

Talking about India, Mumbai is considered a hub of prominent management institutes. There are several top-rated management institutes in Mumbai that offer you an MBA marketing course with an excellent ROI. Here’s a list of concepts and areas covered under the syllabus of these institutes:

1.Business Environment and Management

If you’re looking at how environmental parameters affect a business, this is certainly an important aspect of marketing for you. It helps you gain knowledge about industrial policy, consumer acts, economic planning, import-export policy, privatization, and so on.

Management topics are the first thing that you’ll learn in your MBA marketing institute. It emphasizes you to learn about important management ideas, ownerships, and approaches. Moreover, it also makes you capable of planning and directing marketing campaigns.

2. Data Analytics

With the growing technological advancements in artificial intelligence, Data Analytics has been included in the curriculum of marketing MBA. It teaches you to work with a large volume of business data using the latest programming platforms, visualization tools, and algorithms.

3. Sales Management

Sales management has been a crucial part of Marketing MBA and has existed in the curriculum for a long time. It involves concepts of the sales organization with both theoretical and practical knowledge of sales operations. The module also helps you learn the art of salesmanship.

4. Consumer Behavior

The consumer is considered as the center-stage of marketing, and that’s why there’s a complete module about consumer behavior. In this module, you learn about the group and individual determinants of consumer behavior. It also talks about the change in consumer behavior due to environmental impact.

5. Marketing Management

Marketing Management is the most comprehensive and important module of a marketing MBA. A standard business school in Mumbai will teach you about several marketing aspects such as determining a product’s price, understanding its life cycle, and so on, under this module.

6. Digital Marketing

As the world is getting more and more digital every day, there’s a need for digital experts to support modern-day businesses on the internet. That’s why marketing MBA has started keeping digital marketing as a part of their curriculum in which you learn several topics such as SEO, PPC, SMO, and so on.

7. Statistical Analysis

Marketing MBA courses also allow you to here’s What You Can Expect from Top Management Institutes in Mumbaiarn about statistical concepts and their applications in solving real-world marketing problems. It also covers concepts based on operational research and encourages you to apply them in industrial projects.

The Takeaway

If you want to make a fulfilling career in the business world, a marketing MBA course is certainly a perfect match for you. There are numerous business institutes in Mumbai that offer complete courses with the entire curriculum. Therefore, make sure you begin your preparation right away and begin your path to a successful future quickly.

How Can a Non-Tech Professional Move to Analytics?

January 3, 2020
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| Big Data
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Currently, there is a paradigm shift in the marketplace as many professionals are looking for job roles in analytics, primarily related to fields like artificial intelligence, machine learning, data science, and other subjects. However, there is a misconception that only individuals with an IT or engineering background can build a successful career in analytics. However, as the field evolves, many domains in analytics require more than just technical knowledge, for example, business analytics.

In this article, we will highlight how non-tech professionals can contribute to the field of analytics efficiently. However, before we delve deeper into the ‘how,’ let’s answer the ‘why’ and ‘what.’

Why You Should Consider Making A Career Shift To Analytics

1. Huge Job Opportunities

Data Analytics is considered to be one of the most ‘hot’ jobs in the current market as the demand for analytics skills has increased exceptionally. However, there is a significant deficit on the supply side globally and is not restricted to any one location. Hence, there is a large number of unfilled jobs across the globe due to a shortage of skills.

2. Multi-Industry Opportunities

With the help of analytics, businesses can implement cost-effective solutions and improve decision-making power in multiple development areas, like healthcare, manufacturing, education, real estate. Hence, depending on your interest, you will have the opportunity to select your desired field from a variety of industries.

3. Key Decision-Making Power

In today’s generation, companies understand the importance of making data-driven decisions. Hence, as a data specialist, you will get the opportunity to work with a critical person in the organization. You will also be part of the decision-making team and streamline the layers from top to bottom and coordinate with subordinates to ensure appropriate action is taken on the insights.

4. Work With Reputed Brands

Data analytics started small, being restricted to start-ups and small companies looking for business opportunities. However, with the evolution of the industry, giants like IBM, SAP, Microsoft, HP, and Oracle are exploring analytical research. That being said, these companies will look for professionals who are experts and have experience in the field. So, you can’t expect to secure a job at these firms in the beginning. However, it does create a growth opportunity for you.

5. Become an Excellent Communicator

As a data analyst, your career prospects don’t only depend on how good your programming skills are, rather the combination of your technical skills and your ability to influence companies to take action on your insights to play the primary driving force. Hence, as you keep progressing in the field, your communication skills are sure to improve tenfold.

What Are Analysts Expected To Do

Typically, analysts working in the field of analytics are expected to be proficient with concepts like data mining, statistical analysis, predictive modeling, and multivariate testing. They are also expected to work closely with the management of the company and provide logical and data-driven insights to make business decisions, right from product development to marketing. To break it down in pointers, analysts are expected to:

Gather data from multiple sources
Evaluate problems and opportunities in the business and identify various areas for improvement
Evaluate the feasibility of a solution and possible outcomes using modeling and analysis
Create activity diagrams, use cases, business scenarios, document analysis, and workflow analysis
Study data accumulated from surveys and workshops
Communicate and coordinate with external and internal customers and vendors
Understand the business needs of a customer and create applications and operational processes to fulfill the requirement with analytics and product management skills

To fulfill the requirements above, the analyst is expected to have an in-depth understanding of various engineering concepts and modeling techniques and methods. They are also likely to be able to develop a case and communicate among team members and customers. Lastly, they need to be able to conduct cost and benefit analysis to guide the company towards a high return on investment.

How Can A Non-Tech Graduate Fit Into This Role

The job description can be threatening for a non-tech graduate, like a commerce student, as analytics is a relatively new field of them. However, a commerce student, for instance, can make use of their strong foundation in finance and management to understanding insights from the data and make better decisions. Moreover, their experience of dealing with numbers can play a crucial role in deriving useful information from numerical data. Non-tech professionals looking to move to the analytical industry, need to work on the following skills:

Document creation and training
Understand workflow management process improvement
Gain a thorough understanding of research, analysis and data management
Get familiar with software applications and even technical experience such as coding
Upgrading excel skills

Regardless of how advanced technology and analytics get, businesses will always need human insights to analyze the data and derive insights to make decisions. Hence, more and more companies are looking for experts to understand data and offer data-driven decisions to help their business reach new heights of success. So, it doesn’t matter which field you come from, if you have an interest in data analytics, the time jump the bandwagon is now! All you need to do is register for an analytics course at reputable institutes like N.L. Dalmia and kick-start your career in big data analytics.

Big Data Course: All You Need to Know Before Enrolling to One

December 10, 2019
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| Big Data
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Currently, the world that we live in is ruled by data. Hence, most individuals are opting to undergo some data analytics training to enter this billion-dollar industry. You can choose to be a Data Scientist, Engineer, or Analyst; you need to have proper training and certification that will help you fast-track your career and apply for top-paying jobs.

As mentioned above, it’s not surprising that analyzing data plays a crucial role as we’re living in a data-driven world where 90% of all data created in the last two years alone. That being said, while most enthusiasts are ready to jump the wagon and join this billion-dollar industry, there are certain things you should know before enrolling for the Big Data Course:

What Is Big Data?

Big Data is essentially data but in a large amount. The term Big Data is used to describe a huge collection of data, which is expected to keep growing with time. Due to a large amount of data, none of the commonly used data management tools are able to analyze or store and process the data effectively.

That being said, to get an in-depth understanding of what exactly is Big Data, some historic definitions can be used. For example, in 2001, Gartner released a definition of Big Data, which is still being used to date. The definition states, “Big data is data that contains greater Variety arriving in increasing volumes and with ever-higher velocity. This is known as the six Vs.”

The Six Vs of Big Data

1. Volume

The first to consider when you receive data is to analyze how much of it is there? When it comes to Big Data, high volumes of low-density, and unstructured data needs to be processed and analyzed. As it is unstructured, this data can be unknown, for example, Twitter data feeds, clickstreams on a web page, and others. For certain organizations, depending on the niche they operate in, storing such kind of data amount to more than tens of terabytes of data or even hundreds of petabytes.

2. Velocity

The next V stands for velocity that indicates the rate at which the data is received on an average. Generally, this highest velocity of data streams directly into memory, instead of being written on the disk. On the other hand, when it comes to smart products that are enabled by the internet, the data will be processed in real-time or near real-time, and hence, this type of data required real-time evaluation and action.

3. Variety

The third V stands for Variety, which is basically the different types of data. The most common types of data are structured and unstructured. Structured data is more traditional and preferred as it fits neatly in a relational database. However, as the applications of big data keep increasing, data started becoming unstructured. When it comes to unstructured data, examples like text or audio could require additional preprocessing, which will help decode the meaning of the data and support metadata.

4. Value

To put it simply, data has no intrinsic value. Data only proves to be valuable if a company is able to extract relevant insights to solve a particular problem or meet a specific need. Hence, data acquired value through the impact it leaves on a business and the consumer value insights the data delivers. In order to harness the full value of data, organizations can follow the steps given below:

Ensure you spend enough time analyzing the data by digging deep to derive clear insights, based on which you can develop a strategy
Closely monitor any changes in regulations, especially when it comes to security requirements
Analyze how you can be more transparent with your customers regarding the usage of their data

5. Veracity

The term veracity, when it comes to big data, refers to ensuring the reliability and validity of the insights derived from the data analyzed. This is particularly important as if the data is inaccurate, it is not only useless, but can also result in major repercussions if applied. However, maintaining a balance is crucial as in the quest to obtain veracity you might be over-cautious and wait for perfect, clean data before making any decision – which is extremely impractical.

6. Variability

The last V is for variability, which is the most debated upon concept as it can refer to multiple things. Mostly, variability stands for the inconsistencies in the data that need to be found by anomaly and outlier detection methods. Variability could also refer to the inconsistent speed at which big data is loaded into your database.

The Scope of Big Data in 2020

According to a report published by IDC, the Worldwide Big Data & Business Analytics Market is estimated to grow from $130.1 billion this year to over $203 billion in 2020. The report went on to quote IDC’s Dan Vesset, where he stated that due to the easy access to data, the introduction of the latest technology and colossal culture shift towards making data-driven decisions, the drive for big data and analytics technology and services.

Based on the current growth rate of this big data industry, given below, are a few predictions of the scope of big data in 2020:

1. Ever-Increasing Demand for Data Analytics

Fairly recently, Peter Sondergaard, who was employed at Gartner Research, where he released a statement about Big Data and the importance of data analytics in the modern world. He said that information is the oil of the 21st century, and analytics of that information is the combustion engine.

That being said, the combustion engine is an integral part. Hence, regardless of the tons of the data we are collecting every minute, it is essential that we can understand the data with some data analytics skills. The main question of the hour essentially is, who is responsible for analyzing vast quantities of data and transforming them into valuable business?

2. Applications of Big Data Is Across Different Parallels

Big Data is often considered to be omnipresent, and hence big data has multiple applications across different sectors of industry. According to a study by Wanted Analytics (2015), the biggest significant demand for Big Data professionals is by Professional, Scientific and Technical Services (25%), Information Technology (17%), Manufacturing (15%), Finance and Insurance (9%), and Retail Trade (8%).

3. Career Opportunity & Salary Growth

Due to the different requirements involved, Big Data provides the most versatile career options for those who are looking to join the industry.

Moreover, as most companies, even tech giants like IBM, Microsoft, Oracle, Google, and Pentaho, are making use of the data derived from analyzing Big Data. This ultimately results in increased job opportunities for skilled professionals.

Moreover, as the demand for Big Data grows, the salary package offered to the professionals of this industry grows as well. When it comes to Big Data jobs in India, a fresher with a Master’s degree in Data Science or Analytics can land a job with a package between INR 4 – 10 LPA, depending on their skill set and the company they decide to join. On the other hand, candidates who have 3-6 years of experience can bag a package of up to INR 10 – 20 LPA. Moving to the more senior professionals of the field, employees with over 6-10 years of experience earn about INR 15 – 30 LPA.

Job Opportunities in Big Data

With almost every company looking to benefit from Big Data, professionals who have experience and knowledge in this field are in high demand. The top job opportunities in Big Data include:

1. Data Scientist

There are plenty of opportunities for professionals who are capable of mining and interpreting complex data in large volumes. Essentially, Data Scientists partners with cross-functional IT teams to compile and analyze data and derive insights that are ultimately presented in the form of recommendations and action plans.

2. Data Engineer

A Data Engineer combines concepts from computer science and engineering to analyze and manipulate large volumes of data. Everyday tasks of a Data Engineer include creating and translating computer algorithms into prototype code, developing technical processes to improve data accessibility, and designing reports, dashboards, and tools for end-users.

3. Data Analyst

The job description of a Data Analyst is to gather insights about various topics by creating large-scale surveys. Their job entails recruiting participants, compiling and analyzing the data received and converting the actionable points into traditional charts and reports.

4. Security Engineer

One of the core jobs of a Security Engineer is to plan, avert, and mitigate IT disasters. With the help of computer firewalls, detecting and responding to intrusions, and pinpointing security issues in the system, a Security Engineer is responsible for lessening corporate risk. They are also in charge of creating and implementing test plans for new software and hardware to implement adequate security measures from the beginning.

5. Database Manager

A Database Manager is responsible for managing, performing diagnostics, and repairing databases, whenever required. They are also responsible for reviewing business requests for data, tracking the use of data, and verifying data sources to improve the quality of the data feed.

Skills Required To Get A Big Data Job

As the market is extremely competitive, you need certain skills to ensure you can land a job in this niche. Mentioned below are a couple of skills that can help:

1. Apache Hadoop

Hadoop has entered its second decade, but there has been a steep rise in its popularity in the last 3-4 years. Many software companies commonly use Hadoop clusters. Standard Hadoop components include Hive, Pig, HDFS, HBase, MapReduce, etc. are extremely popular too. Hence, professionals looking to enter the Big Data niche should be proficient with this technology.

2. NoSQL

Traditional SQL database like DB2, Oracle, and others have been replaced by NoSQL databases like Couchbase and MongoDB. These databases are handy when it comes to meeting the needs of big data storage and easy access. NoSQL complements that expertise of Hadoop, and professionals who are well-versed with this technology are sure to find multiple opportunities.

3. Data Visualisation

Tools like QlikView and Tableau that are part of the data visualization are popularly used to decode valuable insights from the data provided from analytics tools. However, using these tools is complex and tough to grasp. Hence, professionals who know how to use them effectively are in high demand, especially in big organizations.

4. Machine Learning

The hottest fields in Big Data currently are Machine Learning and Data Mining. Even though Big Data comprises of multiple components, these two play an essential role when it comes to the success of this field. Professionals who are knowledgeable about machine learning can use their skills to carry out a predictive and prescriptive analysis. As this skill set is rare, professionals with the knowledge of machine learning and data mining are paid exceptionally well.

5. Apache Spark

Replacing complex technologies like MapReduce, Spark is a preferred alternative as it is easy to use and quicker. With its latest developments, Apache Spart has become very popular, with or without Hadoop. With many companies embracing this Apache technology, professionals are proficient with these skills can find multiple high-paying opportunities.

Advantages of Big Data Certifications

If you don’t have the skills mentioned above, don’t fret. Certifications are a great way to make a career shift, and the Big Data niche is no different. Especially in this fast-changing world of technology, with new concepts and technologies being invented almost daily, certifications have become a reliable way to prove competency to companies. Basically, certifications act like a speedy and practical crash course, that allows you to enhance your skill set. Mentioned below are a few certifications you could consider opting for:

1. HortonWorks Certification on Hadoop Developer and Administrator

A new player in the Hadoop distribution market, Hortonworks was founded as a spun-off from Yahoo in 2011 and maintains the Hadoop infrastructure in-house. Currently, HortonWorks is the only vendor that distributes an open-source Hadoop without any cost for any other software.

2. IBM Certified Data Architect- Big data

If you’re looking to pursue your career as a Big Data Architect, you need to have extensive knowledge about technologies and tools and how they can be integrated to solve Big Data business problems. IBM’s website provides detailed information about the skills and knowledge required before giving the exam. The website also provides a list of courses you can choose from.

3. SAS Certified Big Data Professional

To get into the SAS Certified Big Data Professional Program, the candidate must have had at least six months of programming experience, either in SAS or another programming language. It is also essential for you to have knowledge about SQL, Macro, and Advanced Programming.

The academy’s big data certification program focuses on these areas:

Improving data quality for reporting and analytics
Fundamentals of statistics and analytics
Working with Hadoop, Hive, Pig, and SAS
Exploring and visualizing data

You can read more or apply for this certification from the N.L.Dalmia website.

Conclusion

Regardless of how advanced technology gets, the need for human insights cannot be removed from the equation. There is a serious need for skills professionals who can understand data and derive useful insights from a business point of view. A professional with Analytical skills can master the ocean of Big Data and become a vital asset to an organization, boosting the business and their career.

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