Best Big Data Examples for Beginners

Today, we have hundreds of courses in big data science. But, a majority of them focused on the technology side of the applications rather than educating the analysts on how these big data certification courses actually benefit the different industries and departments within an organization. So, how did we arrive at a point in 2022 where big data certification courses are foreseen as the stepping stone to a solid career in data science, AI and IT Operations? 

Let’s find out.

Last 5 years, Big Data professionals have made a strong impact on the economy

Globally, the big data industry has been growing at a significantly impressive rate, ranging between 8% and 15% CAGR. In the last 5 years, big data professionals have emerged as the most sought after business talent in the Cloud and IT Automation industries, garnering the moniker of “sexiest job title” for different roles such as data scientists, AI engineers, and so on. In 2022, the big data industry is expected to earn a revenue of 1 trillion USD, with a lion’s share coming in from the big data applications set up for Digital Marketing and Sales, IT Security, Manufacturing, Blockchain, and much more. With investments, mergers, and acquisitions flying into the thin air, the strong currents of change are in place for big data analysts in the coming years.

In less than 5 years, big data and analytics have become the mainstream approaches to developing newer platforms for different types of business operations. If you are working in the data science industry and looking to advance your career with big data applications, this article is meant for you. 

Top industries that train with big data

We have identified the top big data applications specific to the industries and enterprise platforms. These are:

  1. Big Data in Marketing
  2. Big Data in Human Resources Management (HRM)
  3. Big Data in Finance and Banking
  4. Big Data in Healthcare
  5. Big Data in Manufacturing 

Big Data in Marketing:

Marketing has moved to online business completely. You would no longer find much happening in the offline mode unless the business is itself isolated from the online environment. Be it a local business or a global conglomerate, marketing teams around the world use Big Data architectures to gain smarter insights about their market position, competition matrix, product segmentation, and brand image. All of these are used to listen to customers and partners to develop what we call as “personalization”, “customer experience”, and “social media listening.” 

The routine applications for big data techniques involve the creation of a holistic 360 degree view of the audiences online using user data acquired from online first party data sources as well as third party KYC acquisition platforms. From brand awareness campaigns to running influencer tactics on social media channels such as YouTube, Instagram, and TikTok, Big Data in marketing delivers great results with optimized cost of customer data acquisition. 

Big Data in Human Resources / HR:

HR is the backbone of a modern hybrid working organization. The employee data management is one of the most complex jobs that a data analyst would ever take up in the career lifecycle – because employees keep changing their biodata and they keep moving places or keep transitioning from one role to another even if they are meant to be working in the same company. We have all been witness to how HR principles had to undergo a seismic shift during the pandemic where 90% of the workforce suddenly had to switch to “work from home” and remote working conditions. These, of course, led to the transition of the big data projects in HR. For instance, HR teams are using big data dashboards to upgrade their visibility of employee conversation, engagements, job satisfaction levels, appraisals, performance management, and people analytics. Today, it wouldn’t be wrong to say that HR teams are at par with marketing and sales teams when it comes to generating ROI from their Big Data investment.

Big Data in Finance:

Big Data analytics is a fast growing sector in the data science industry. In Finance, we have seen how financial services companies and banks are using data to transform their existing processes. For professionals pursuing big data certification courses in the finance industry, there is ample scope with respect to challenges they can solve by fundamentally deploying newer concepts such as image recognition, character recognition, video surveillance, and facial recognition / biometrics. Deep learning concepts are used in credit reporting and fraud monitoring specific to credit card and insurance sectors. For lending companies, AI and machine learning applications are making a robust presence through customer analytics, risk management, fraud analysis, and chatbot supports.

Big Data in Healthcare:

Big Data in healthcare is a solid reason to revisit the way medicine and vaccines are administered to the general population. In the last 3 years, we have witnessed how healthcare has moved from a general model of medication administration to a more personalized care. Today, it has become possible for doctors to diagnose critical illnesses among patients using advanced AI and machine learning diagnostics tools without even touching the patient. On the other hand, it is possible for the patients to reach out to the healthcare providers for basic treatments for cough, cold, vaccination, neurological disorders, pain relief and pre-surgical consultation. Even for elderly and pregnant women, who might find it hard to visit a clinic during the pandemic situation, rely on mobile apps built using big data architecture for their basic consultation before and after tests.

Big Data in Manufacturing:

Like healthcare, the manufacturing industry is benefitting from the involvement of big data applications, particularly for automation, driverless equipment handling, automated software embedding, AR VR, and AI based process control and supply chain management. With big data science, it is easier for manufacturing companies to collect and visualize how material, machine, and manpower function together as a unit, optimizing the full cycle of product delivery. Companies like AWS, Google Cloud, IBM, and Salesforce are providing big data analytics to improve manufacturing.

So, where is the big data certification course heading?

Big Data entails working with a large volume of data that has different characteristics and properties as far as expectations and nature of modeling are concerned. The ability to work with a large volume of data can be acquired by putting automation and machine learning algorithms at the center of data management handling big data projects. This has given a chance to grow ‘as a service offering from Big Data companies that leverage data modeling and analytics to drive fundamental results for different types of businesses.

Why Big Data as a service is so important?

Big Data as a service has been around in the industry for some time now, and it has already provided ample reasons to paddle the way forward with big data management and analytics tools to garner better business outcomes. When it became evident in the mid 2015 that it would be impossible to sustain business results without throwing open the challenge of big data and business intelligence to the business analysts, the market opened up significantly for investors and researchers targeting emerging technologies such as AI, machine learning, data analytics, automation, cloud computing, and 5G.