You may build efficient Big Data solutions for a variety of business disciplines using a range of software and hardware setups, from social media and mobile applications to intelligent analysis and visualization of business data. The compatibility of new tools with commonly used business databases is a significant benefit of Big Data, which is crucial when working on cross-disciplinary projects like, for instance, organizing multi-channel sales and customer service.
We will discuss the implementation strategy in more detail later in the article, where you’ll discover the cornerstones of Big Data and why these solutions have become so popular among businesses of various sizes and areas.
Big Data Definition
Big Data, which first appeared in the late 2000s, refers to alternative database management systems and Business Intelligence class solutions. It is a term used to describe structured and unstructured data of enormous volumes and significant diversity that can be processed effectively by horizontally scalable software tools.
You can also employ a more straightforward definition: Big Data is a collection of technologies designed to achieve three tasks:
- To process larger volumes of data compared to “standard” scenarios.
- The ability to work with data that arrives fast and in great amounts. That is, there is not only a lot of data, but it is growing all the time.
- Work with structured and unstructured data in diverse ways.
The value of Big Data is the information that the company receives after “running” the data through the analysis algorithm. It must be validated by an analyst or a specialist in the relevant field of human activity (for example, medicine) before it can be utilized to improve the processes in the organization, namely, to increase profits or reduce expenses.
Who Needs Big Data for Their Business
Logical questions arise, such as how information may be employed (if Big Data consists of hundreds of thousands of terabytes)? What role does Big Data play in marketing and business?
- Conventional databases are incapable of storing and processing massive amounts of data.
- This primary task is solved by Big Data. It stores and handles a vast volume of information successfully.
- It structures information from diverse sources (video, photos, audio, and text documents) into a single, clear, and convenient form.
- It analyzes and generates reliable forecasts based on organized and processed data.
Simply put, any marketer who knows that by studying a vast quantity of information (about you, your company, your competitors, and your industry) can achieve excellent results:
- Complete understanding of your organization and your business;
- Examine your competitors. And this, in turn, will allow you to reach a competitive advantage.
- Find out more about your customers.
Benefits of Big Data
There are numerous examples of how Big Data can help you function more efficiently.
Microsoft and Siemens collaborated to create “smart” X-ray equipment. The tool takes a picture and simultaneously sends it to the cloud and the doctor for analysis. The cloud features an image analysis system based on artificial intelligence that examines the generated image and constantly learns (machine learning). The doctor and the system make a diagnosis simultaneously; if there are significant differences, the doctor is notified that the diagnosis has to be double-checked. Sometimes the system makes the wrong decision, but it often helps to see hidden facts that a person does not detect.
Big data in retail and distribution allows for more efficient stock replenishment by identifying the relationship between demand for specific categories of goods and weather or events in the surrounding area.
The benefit of Big Data varies depending on the business or even the sort of activity. The critical thing to remember is that Big Data enables you to take precise action and frees up human resources for more complex and imaginative work.
For instance, a business performance analyst no longer needs to deal with the tediousness of manual computation as they can use processed data thanks to the introduction of machine processing algorithms. Machine algorithms can act as a safety net for professionals whose work requires extra attention (doctors, attorneys) and focus their attention solely on situations that stand out from the general bulk of results.
How Is It Done?
Working with Big Data entails collecting data, organizing the obtained information using reports and dashboards, producing insights and contexts, and formulating action recommendations. Because dealing with Big Data involves high costs for data collecting, the outcome of which is uncertain in advance, the essential goal is to have a clear grasp of what the data is needed for rather than how much data is accessible. In this case, data collection becomes a method of gathering information that is required to complete specified activities.
The organization must assess the investment case in order to properly decide whether to deploy Big Data solutions, which can be very challenging at times owing to many unpredictable factors.
And so, proper planning of your initial steps is critical:
- First, define one specific business challenge for which Big Data technologies will be applied; this problem will form the heart of determining the fidelity of the chosen concept. You should focus on gathering data for this specific assignment, and during the proof of concept, you will be able to employ various tools, procedures, and management methods that will help you to make more informed decisions in the future.
- Second, a company lacking in data analytics expertise and experience is unlikely to be able to implement a Big Data project successfully. The necessary knowledge is always derived from prior experience in analytics, which is the primary element influencing the quality of data work. Data culture is crucial because information analysis frequently shows the hard truth about the business, so accepting this fact and working with it necessitates developing data-working skills.
- Third, Big Data technologies’ value comes from their ability to provide insights. Good analysts continue to be in scarce supply in the market. Data analysis is a tool for achieving business objectives and comprehending the value of Big Data necessitates a proper behavioral model and an awareness of one’s own activities. In this case, Big Data will supply a wealth of important information about consumers, allowing for sound business decisions.
It makes sense to gather data even if you aren’t yet capable of settling on a specific goal. After all, even when the objective is obvious, the algorithms will still require information to “feed” for analysis. Thus, there should be a lot of it. In addition, compared to data analysis systems, storage space costs are now among the lowest.
Core Steps for Big Data Implementation
Let’s find out the core steps for Big Data implementation.
Find a Dedicated Team of Professionals
It’s great if you already have a dedicated team of experts that can handle the project. If not, begin by seeking such a team — but keep in mind that they should have the expertise needed to transform your vision into reality.
Identify your Data Sources
You will need to find additional sources of data that can be used to gather information. At this point, identify, rank, and assess them.
By the way, so-called data lakes can be used to store both structured and unstructured data. Unlike a data warehouse, such lakes offer a flat architecture for data storage. As an alternative, you can build and deploy data lakes utilizing on-premises or cloud infrastructure.
Establish a Connection Between Data Sources and Your Customers
One of the best things you can do is connect data sources to your customer base. For example, by using coupons and distributing them among your customers, you can solve two problems at once: make your customers happy and collect their information.
Use Your Customers’ Data to Benefit Your Business
Data-driven decisions are the best decisions. Make sure that you’re using your customers’ information to improve the quality of your products and services. Now, incorporate the data into all levels, from marketing to product development.
One of the most crucial steps in the analysis process is testing, measuring, and learning. Always test the underlying hypotheses while gathering further data to determine how to proceed.
The volume of data has greatly expanded with global technological advancement. Big Data technologies allow for the efficient and speedy use of this wealth of data. They aid in the optimization of numerous procedures for governmental institutions and company representatives while also providing end users with higher-quality services. Contact us if you want to learn more about implementing a Big Data solution for your business.