Big Data Analytics
Darshika Srivastava
Associate Project Manager @ HuQuo | MBA,Amity Business School
What is Big Data Analytics?
Big data analytics is the process of using advanced analytical techniques against extremely large and diverse data sets, with huge blocks of unstructured or semi-structured, or structured data. It is a complex process where the data is processed and parsed to discover hidden patterns, market trends, and correlations and draw actionable insights from them.?
The following image shows some benefits of big data analytics:
Big data analytics enables business organizations to make sense of the data they are accumulating and leverage the insights drawn from it for various business activities.?
The following visual shows some of the direct benefits of using big data analytics:
Before we move on to discuss the use cases of big data analytics, it is important to address one more thing – What makes big data analytics so versatile?
Core Strengths of Big Data Analytics
Big data analytics is a combination of multiple advanced technologies that work together to help business organizations use the best set of technologies to get the best value out of their data.
Some of these technologies are machine learning, data mining, data management, Hadoop, etc.
Below, we discuss the core strengths of big data.
1. Cost Reduction
Big data analytics offers data-driven insights for the business stakeholders and they can take better strategic decisions, streamline and optimize the operational processes and understand their customers better. All this helps in cost-cutting and adds efficiency to the business model.?
Big data analytics also streamline the supply chains to reduce time, effort, and resource consumption.
Studies also reveal that big data analytics solutions can help companies reduce the cost of failure by 35% via:
2. Reliable and Continuous Data
As big data analytics allows business enterprises to make use of organizational data, they don’t have to rely upon third-party market research or tools for the same. Further, as the organizational data expands continually, having a reliable and robust big data analytics platform ensures reliable and continuous data streams.?
3. New Products and Services
Because of the availability of a set of diverse and advanced technologies in the form of big data analytics, you can take better decisions related to developing new products and services.?
Also, you always have the best market and customer or end-user insights to steer the development processes in the right direction.
Hence, big data analytics also facilitates faster decision-making stemming from data-driven actionable insights.
4. Improved Efficiency
Big data analytics improves accuracy, efficiency, and overall decision-making in business organizations. You can analyze the customer behavior via the shopping data and leverage the power of predictive analytics to make certain calculations, such as checkout wait times, etc. Stats reveal that 38% of companiesuse big data for organizational efficiency.
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5. Better Monitoring and Tracking
Big data analytics also empowers organizations with real-time monitoring and tracking functionalities and amplifies the results by suggesting the appropriate actions or strategizing nudges stemming from predictive data analytics.
These tracking and monitoring capabilities are of extreme importance in:
6. Better Remote Resource Management?
Be it hiring or remote team management and monitoring, big data analytics offers a wide range of capabilities to enterprises. Big data analytics can empower business owners with core insights to make better decisions regarding employee tracking, employee hiring, performance management, etc.?
This remote resource management capability works well for IT infrastructure management as well.?
7. Taking Right Organizational Decisions
Take a look at the following visual that shows how big data analytics can help companies take better and data-driven organizational decisions.
Now, we discuss the top big data analytics use cases in various industries.
Big Data Analytics Use Cases in Various Industries
1. Banking and Finance (Fraud Detection, Risk & Insurance, and Asset Management)
Futuristic banks and financial institutions are capitalizing on big data in various ways, ranging from capturing new markets and market opportunities to fraud reduction and investment risk management. These organizations are able to leverage big data analytics as a powerful solution to gain a competitive advantage as well.?
Take a look at the following image that shows various use cases of big data analytics in the finance and banking sector:
Recent studies suggest that big data analytics is going to register a CAGR of 22.97% over the period of 2021 to 2026. As the amount of data generated and government regulations increase, they are fueling the demand for big data analytics in the sector.
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2. Accounting?
Data is Accounting’s heart and using big data analytics in accounting will certainly deliver more value to the accounting businesses. The accounting sector has various activities, such as different types of audits, checking and maintaining ledger, transaction management, taxation, financial planning, etc.?
The auditors have to deal with numerous sorts of data that might be structured or unstructured, and big data analytics can help them in:
Using big data analytics will also improve regulatory efficiency, and minimize the redundancy in accounting.
3. Aviation?
Studies reveal that the aviation analytics market will hit the 3bn USD by 2025 and will register a CAGR of 11.5% over the forecast period.?
The major growth drivers of the aviation market are:
Recent trends and changes in the Original Equipment Manufacturer (OEM) and user segment of the aviation industry One of the most bankable big data analytics opportunities in the aviation industry is cloud-based real-time data collection and analytics, which requires diverse data models.?
Likewise, big data analytics has a huge potential in the airlines’ industry as well, improving basic operations, such as maintenance, distribution of resources, flight safety, flight services, to business goals, such as loyalty programs and route optimization.?
The following image shows the various points of data generation in the aviation industry (flights only), that can be a valid use case for big data analytics:
4. Agriculture
UN estimates reveal that the world population will hit the 9.8 billion mark by 2050 and to fulfill the food demands of such a large population, agriculture needs modification. However, the climate changes have not only rendered the majority of farmlands unfit for farming, but have also impacted the rainfall patterns, and dried a number of water sources.?
This means that apart from increasing crop production, farmers have to improve the other farming-related activities.?
Big data analytics can help agriculture and agribusiness stakeholders in the following ways:
Some of the ideal case studies in this regard are:
5. Automotive
Be it research and development, or marketing planning, big data analytics has a huge scope in the automotive industry that is a combination of a number of individual industries. Being a core infrastructure segment empowering a number of crucial public and private ecosystems, the automobile sector generates huge loads of data every single day!
Hence, it is one of the most critical use cases for big data analytics.
Some common applications are:
Take a look at the following visual to have an overall idea of the big analytics use cases in the value chain of the automotive industry:
6. Biomedical Research and Healthcare (Cancer, Genomic medicine, COVID-19 Management)
Recent stats reveal that the big data analytics market in healthcare will be around 67.82 bn USD by 2025. Healthcare is a huge industry generating mountains of data that is extremely crucial for the patients, medical institutions, insurance companies, government, and research as well.?
With proper analysis of huge data blocks, big data analytics can not only help medical researchers to devise more targeted and successful treatment plans but also procure medical supplies from all over the world.?
Organ donation, betterment of treatment facilities, development of better medicines, and prediction of pandemic or epidemic outbreaks to contain their ferocity – there are multiple ways big data analytics can benefit the healthcare industry.
Take a look at the following image for a better understanding:
Also, big data analytics is playing a huge role in COVID-19 management by predicting the outbreaks, red zones, and facilitating crucial data for the frontline workers.?
Finally, when we talk about Biomedical research, big data analytics emerges as a powerful tool for:
The biomedical research and healthcare industry is a huge use case for big data analytics and the applications can themselves form a topic of lengthy discussion.?
Various applications of big data analytics in biomedical informatics:
7. Business and Management
95% of businesses cite unstructured data management as a major problem and 97.2% of business organizations are investing in AI and big data to streamline operations, implement digitization and introduce automation, among other business objectives.?
However, the business organizations suffer from multiple data pain points, such as:
Big data analytics can thus be a knight in shining armor for business process streamlining and management with its massive capability set.?
Business owners can take more targeted, data-driven, and smart decisions based on the data insights provided by big data analytics, and do much more, as ideated in the following visual:
8. Cloud Computing?
45% of businesses across the globe are running at least one big data workload on the cloud, and public cloud services will drive 90% of innovation in analytics and data.?
Cloud computing has many challenges, and security is one of them. In fact, security is becoming a major concern for business organizations across the world as well. ‘
Also, big data analytics has rigorous network, data, and server requirements that persuade business organizations across the globe to outsource the hassle and operational overloads to third parties. It is spurring a number of new opportunities that support big data analytics and help organizations overcome architectural hurdles.