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The Role of Big Data in Modern Businesses

CIAT. Edu offers an Associate of Applied Science in Business Data Analytics and an Applied Bachelor’s Degree in Software Development – Data Analytics Concentration.

Data can be used and manipulated at the touch of a button for most modern businesses. However, the ability to use that data and interpret the information is easier said than done. New careers are being forged every day to solve that problem.

Data analytics is the process of storing, organizing, and analyzing data for future business decisions or processes. Every truly modern business is in a race to incorporate data and analytics into their day-to-day business decisions to increase efficiency and decision effectiveness.

But there is a long way to go. A study by NewVantage in 2021 discovered that only 39% of executives believe their organization is using their data in the correct way, and only 24% see their company as being “data-driven.”

This is a primary reason why data analytics careers are growing in number and salary faster than nearly every other field. Businesses demand data analysts to help them bridge the gap between the present and the future.

What is Data Analytics in Modern Business?

A data-driven company can be described as a business that uses data to:

  • Describe and analyze the company’s strengths and weaknesses
  • Prioritize investments 
  • Allocate resources
  • Build KPIs to manage progress
  • Become more data-driven and competitive

Data analytics can also help businesses study the effectiveness of their current workflows, analyze different outcomes of processes, automate workflows, and refine them over time to keep them up-to-date.

There are three types of business analytics that can be used to gather this information, and they are:

  • Descriptive Analytics – what has already happened
  • Predictive Analytics – what could happen 
  • Prescriptive Analytics – what should happen

Big data is defined as the use of large volumes of aggregated data points to predict outcomes, determine changes in trends, and target audiences.

What is Big Data and How Is It Used in Business?

To put it in its absolute simplest terms, big data is defined as larger, more complex data sets, particularly data from new sources. These data sets are so large that they cannot be handled by traditional data processing software.

Though systems that store and process large quantities of data are commonplace in data management, big data is uniquely classified by “the three V’s:”

  • Volume – Unlike other forms of data management, big data involves a colossal amount of data processing.
  • Velocity – The speed at which the data is collected and processed. With big data, this happens at an extremely quick pace.
  • Variety – The many different types of data being collected and processed.

These terms were first coined in 2001 by analyst Doug Laney, an employee of Meta Group Inc.

With the rise of big data, two more V’s have emerged in recent years: value and veracity. The value reflects how much the data could be worth to a company, while the veracity simply refers to the accuracy of the data.

While there is no specific size limit required to be officially considered big data, big data deployments often involve exabytes of data collected and processed over a period of time.  

Big data can come from a number of sources, including customer databases, emails, medical records, and social media networks. It can also include machine-generated data, such as sensor data from manufacturing equipment and other industrial machines.

Big data will often incorporate external data as well, including weather and traffic patterns and geographic information. Audio and video files are frequently included as forms of big data, as streaming data is often processed and collected to aid certain companies with big data applications.

What makes big data so important is how it can be used in predictive modeling to help businesses understand patterns and trends that occur when people interact with various systems and each other.

Companies and businesses can use big data to gain a better understanding of the preferences of their customer base, aiding them in creating better marketing strategies, customer service, and other customer-focused actions that will ultimately lead to more business.

Using big data is crucial for companies to maintain a leading edge over their competition. New entrants into an industry rely heavily on big data to innovate and compete with well-established companies.

Businesses that use big data most effectively will hold a large advantage over those that do not, as they will be able to make faster and more informed business decisions. These days, the use of big data is found in just about every sector, from IT to pharmaceuticals.

Streaming companies like Netflix or HBO use big data to recognize and predict customer demand. By identifying key attributes of past and current programs and comparing those to their current success, these streaming companies can successfully build predictive models for new programs and movies, giving them an accurate idea of how successful this new product is likely to be.

Aiding product development is a common goal of big data management, and any popular company will employ it to stay ahead of the curve.

Big data is also extremely helpful in increasing the value of the customer service of a company. Through the collection and processing of data through social media, website visits, and other sources, businesses can improve the quality of their customer service experience. Faster ticket times, personalized offers, and the ability to handle issues proactively are all due to big data.

Security and IT teams employ big data frequently to aid their efforts. These days, hackers tend to consist of large teams of experts, unlike the single lone-wolf hacker frequently portrayed in movies.

Big data helps to identify patterns left behind by hackers that tend to indicate fraud or security breaches, allowing security and IT teams to react to the problems significantly faster than they would be able to otherwise.

With its increasing use and importance in running a business, big data is creating new opportunities on its own. There is an increasing demand for companies that are able to accumulate and analyze industry data.

These companies hold an immense amount of data about supply and demand, customer intent, service and products, and more. These businesses are in high demand from other companies looking to take advantage of all the available data. 

How are Data Analytics and Big Data Important to Modern-Day Programmers and Developers?

The role of programmers and developers in modern-day business is both increasingly important, and increasingly reliant on data analytics.

Data-adept developers are valuable because they help executives make difficult decisions to help drive organizational effectiveness, efficiency, and profitability.

Data analysts and back-end programmers work closely together to interpret data and then act on it based on decisions that are made from patterns and trends identified. 

Front-end developers can use data to determine how a website or platform should be created and maintained to keep up with current trends and competition.

Beyond using data to construct, data visualization is also essential in all aspects of business. Tools like Tableau and MySQL empower developers and software engineers to communicate more effectively with decision-makers.

These days, software developers are required to know more than just how to program in their chosen languages. Developers now must be experts in collaboration, relying on communication between various teams, their managers, and often even other companies.

With the increasing use of big data in software development, this type of collaboration is becoming more and more streamlined every day.

While it is used in myriad ways by a multitude of different types of companies, big data’s application in software development covers almost every category. From customer service to product development, correctly analyzing big data provides developers information about consumer habits and preferences, potential bugs or errors, key functionality points of an app or program, and much more.

Taking advantage of the availability of this information allows a team of developers to streamline much of the research and development, as well as correctly identify and avoid potential user issues before they ever occur.

A software development team that properly utilizes big data will end up with a product that users are more likely to prefer, and they will be able to get it into the hands of the customer faster than their competition.

Outside of developing their own applications or programs, developers are increasingly being called upon to program predictive analytics systems that can be used in other software applications and business processes.

Many web services rely on such programs to collect and analyze the correct data so that they can provide the insights necessary to give that company an edge. The increasing demand for this type of software development is leading to a tremendous influx of innovation and collaboration.

It has been predicted that the big data market size will double by 2027. With such a rapidly increasing demand for big data management, the demand for developers who have the knowledge to utilize this will increase as well, and will only continue to grow.

Businesses Also Use Big Data, AI, and Machine Learning to Know Their Customers Better

High-performing firms such as Netflix and Amazon use big data, AI, and machine learning that relates to audience segmentation. 

Streaming platforms like Netflix use data analytics and AI to make informed decisions on the type of content to invest in for the future. By analyzing watch data in aggregate and cross-referencing it with account data like gender, age, and location, Netflix is using machine learning to make more accurate predictions on what content performs best, and what should be produced down the line.

Further information on the Netflix case study that relates to AI and Machine Learning can be found here.

Similarly, Amazon is using machine learning for several business processes, including:

  • Improving customer experience
  • Boosting productivity
  • Optimizing business processes
  • Speeding up innovation

Amazon’s AWS platform also offers these machine learning tools as a service that anyone can use.

Further information can be found in the Machine Learning on AWS article here.

The most competitive firms in the world agree that data analytics and AI are the way of the future. This is reflected in the demand for data analysts, data scientists, and AI experts.

Fortunately, educational institutions are similarly ramping up their investment in data analytics.

Data Analytics As a Career

Thousands of schools now offer specialized training in data analytics.

For example, CIAT offers multiple different programs, like:

These courses and certificates will help you learn the skills necessary to advance in data analytics, develop your knowledge, and become a competitive job-seeker in the field.

A data scientist is responsible for a wide range of operations, including:

  • Querying data
  • Mining data
  • Data cleansing
  • Examining and interpreting data trends
  • Preparing reports
  • Summarizing data sets
  • Collaborating with pertinent stakeholders

Data scientists are some of the most sought-after professionals in the US, commanding an average salary of $100,560 per year as of 2022.

The potential to continue to learn new reporting functions or tools is endless in this field and is always needed within any corporation, large or small.


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