3 Reasons To Implement Big Data Analytics
In today’s business and technological world, the importance of ‘data’ is indispensable. ‘Big data’ refers to the large chunk of raw data gathered, stored, and analyzed by organizations to derive strategic decisions. Moreover, the concept of big data evolved at the beginning of the 21st century, and now every business firm is using big data tools and technologies.
But it is interesting to note that, even before using the term big data, organizations were using this concept by collecting data in basic spreadsheets, feedback forms, and graphs to track business trends and customer insights. But, the only difference is, now we are using the right big data tools and data management systems, and analytics to transform these unstructured data into powerful business insights.
What is Big Data?
Big Data refers to the bulk data gathered from IoT devices, social media platforms, weblogs, sensors, etc. These collected data can be structured, semi-structured, or unstructured. Businesses use Big Data to generate valuable insights. Companies are using this data to refine their marketing strategies, techniques, and campaigns. Companies in machine learning projects also use it to train machines, predictive modeling, and other advanced analytics operations.
Why Big Data?
In fact, the intervention of Big Data has enhanced organizations to deliver better outcomes by improving the bottom line by using the information extracted from these Big Data tools. Also, it is being estimated that 93% of companies have rated Big Data as “extremely important.” Above all, leveraging Big Data analytics help organizations to utilize their full potentials and use strategic values to maximize their assets.
It helps organizations to:
- Optimize workforce planning and business operations
- Analyze existing marketing trends
- Predict future trends
- See What, When, Where and What products their customers buy
- Improve loyalty programs
- Identify cross-selling and upselling opportunities.
- Stand more competitive and innovative.
- Identify and improve defects in the company’s supply chain
- Discover new sources of revenue
- Put forth new targeted promotional information
Organizations use Big Data to become more customer-centric, as they can identify and analyze their customers’ requirements, who their customers are, and why people use their products. Moreover, this can also be used with Machine Learning for creating market strategies based on predictions about customers. Analyzing historical and real-time data help businesses to improve their service. Understanding the customers help organizations to be more competitive and innovative. It allows them to stay updated with the latest business trends.
Types of Big Data Analytics:
Businesses are leveraging different types of data analytical tools to extract informational insight from their data. Here are some most relevant types of Big Data Analytics:
- Prescriptive Analytics
This data concept provides organizations with a specific solution to eliminate a future issue or capitalize on a promising trend. This type of analytics provides the organization with a laser-like focus to answer a particular problem. Hence, it gives organizations the best way to approach a future opportunity or avoid prospective risks.
- Predictive Analytics:
Predictive Analytics uses historical or past data to predict the future. This concept uses various methods such as data mining, big data, machine learning, statistical modeling, and other means to draw predictions regarding future business trends. Organizations can rely on this data to forecast business trends and behaviors.
- Descriptive Analytics:
Descriptive Analytics gives in-depth and meaningful insights by observing the historical data. This type of Big Data acts as a preliminary stage of data processing that helps create an overall summary based on the historical information. In other words, this provides meaningful data that can be utilized for further analysis.
- Diagnostic Analysis:
Data scientists commonly use this technique to analyze the reason behind ‘Why’ something happened. In this method, historical data can be used with other data to find the solution behind why certain things happened. Hence, this approach is beneficial in the sales cycle for identifying customer behavior and product preferences.
Reasons to implement Data Analytics:
- Customer experience
Identifying customer behavior is inevitable to any business. In fact, this can be done accurately by using big data analytics tools.
Using Big Data Analytics help organizations to learn:
- What their customer requirements are
- Who their customers are
- What is the taste of their customers
- Where the business is missing out on conversions
Big Data and analytics tools collate and interpret a bulk amount of data to extract insightful insights about customers. Also, this data let organizations gather more solutions to their marketing questions each day and optimize marketing strategies and campaigns accordingly. The more you are aware of your customers, the more your business turns out to be competitive.
- Optimizing business processes
Firstly, Big Data Analytics helps businesses to stay ahead of the curve by identifying opportunities and rectifying inefficiencies in business practices. For example, big data analytics can help you identify your social media profiles and reach your right audience, and your email strategy is not reaching well. Thus, using big data can help you determine which company culture has the right impact or can cause a considerable turnover.
Furthermore, the knowledge gained from the data collected ensures you spend the budget most appropriately and less on the things that don’t work. For instance, fleet management systems and supply chain management are some industries making the proper use of these tools. Geographic sensors track the vehicles in real-time; routes can be optimized based on live data and traffic information.
- Empowering the next generation
As technology is progressing, the impact of big data analytics can create a revolution for businesses. This technological innovation can contribute agility and innovations to companies and also encourages technology leaders to deliver better for the next generation. Big data tools can enhance the team members by making consequential decisions rapidly based on the data gathered. In other words, this approach helps in building an agile business environment that is ready to suit the latest trends.
Earlier, as there existed limitations due to poor analytics processes, businesses could access only a small amount of data available to them. But now, this powerful technology has empowered organizations to answer critical questions and accomplish more with the data they gathered.
In conclusion, We can conclude that Big Data allows businesses to make more informed decisions and business strategies by deeply understanding their customer requirements. This approach helps companies to achieve success and stay ahead of their competitors. It plays a significant role in shaping the organization. Finally, there exists a massive demand for big data analytics in various fields and industries, as they get a chance to learn about business opportunities.