Big Data Analytics – Benefits and Uses That Businesses Can’t Do Without

Big Data Analytics – Benefits and Uses That Businesses Can’t Do Without

By Stiliyan Neychev

December 15, 2023

In today’s fast-paced world, businesses need all the help they can get to stay ahead of the competition. As they continue to grow and expand, companies start gradually generating more and more data – both structured and unstructured. That’s why they need to find new and innovative ways to stay ahead of the curve.

And that’s where big data analytics come in – providing insights that can help businesses improve their products and services and better understand their customers. It is frequently utilized to identify what is working and what is not in all sorts of fields, such as retail, finance, manufacturing, health care, education, and many more.

But what are the benefits of big data analytics? And more importantly, how can businesses use it to their advantage? Well, with this article, we aim to tell you all about that and more, so keep on reading to find out!

What is Big Data Analytics?

If you’re new to Big Data Analytics, it’s the process of collecting, storing, managing, and analyzing data with the goal of discovering interesting patterns and insights. This is done by using statistical and computational methods to model relationships between multiple variables.

You can easily identify the “Big Data” part through the five V’s: value, volume, variability, variety, and velocity. So, in short, big data analytics is quite complex! Therefore, figuring out all the data your business generates requires both analytical skills and innovative technologies.

Now you know that Big Data Analytics can make your company quite profitable by capitalizing on your data, thus enabling you to make more informed decisions. But here we hear you say, “Why does that matter? My team and I are perfectly capable of making decisions without investing in fancy tech.”

Well, sure, Excel can carry you to a certain point. But as we mentioned earlier, companies are generating more data every day through various sources, both internal and external. At some point, managing and keeping track of it all is like trying to keep hyperactive dogs in a bathtub – impossible!

You see, companies are starting to look beyond simple analysis and massive data sets as solutions, seeking more advanced approaches. And as it so happens, Big Data Analytics is a form of advanced analytics in and of itself. It offers crucial predictive analytics and models that give businesses the ability to uncover trends and develop new strategies – both of which are critical in a competitive marketplace.

What are the benefits of Big Data Analytics?

So, now we know that analytical tools are necessary to progress in this digital era we live in. Also, now we know that Big Data Analytics can provide businesses with a wealth of information, help them make better decisions, and provide a competitive advantage. So, is that all in terms of the benefits of this approach? Well, no! But benefits as a whole are subjective and will vary from business to business and from industry to industry. So, there’s nothing set in stone as far as we know, but three benefits stay relevant and true no matter the field.

Real-time Analysis

This benefit is a key point in all business intelligence technologies and approaches, but it rings even truer for Big Data Analytics. Generally, using some platform to apply some data visualization and then making a decision based on the rough observations is simple enough that most companies have been doing it for ages. However, this task becomes infinitely harder when we add the concept of big data to the equation.

Suddenly, departments take considerably more time to generate reports and showcase new insights, which affects your company’s sales, adaptability, and competitiveness. That’s because we’re not just dealing with a bit more data here; we’re dealing with massive amounts! So massive, in fact, that it impacts your decision-making abilities. So, what do you do?

Well, you utilize Big Data Analytics to have a way to constantly crunch and analyze all the data being gathered. This way, businesses stay competitive, react quicker to unforeseen circumstances, and improve the overall quality of their decisions, because more data leads to more accuracy in the grand scheme of things.

Client Acquisition and Retention

When it comes to market intelligence – Big Data Analytics is a real winner. By leveraging Big Data Analytics tools, companies can analyze and segment clients in a more comprehensive manner. This enables them to see how their products and services are interacted with and refine them based on the segmented groups’ actions and needs.

Additionally, the data-driven algorithms that come with Big Data Analytics can help increase customer satisfaction by providing all the insights to generate an enhanced customer experience. This includes observing client patterns to determine service viability, future development directions, success measurement, and more.

If all this sounds too good to be true, then how about some real-life examples? Leading companies like Amazon, Netflix, Google, and even Spotify have been using Big Data Analytics in the form of personalization engines and predictive analytics. They’re used to generate client loyalty by evaluating their customer insights and providing an experience based on needs rather than wants.

Risk Management

There are lots of risky situations present in a business’ daily workflow, regardless of the industry. That’s why to mitigate some of these risks, people have been turning to data for centuries (or since the 19th century technology-wise). But you can’t solve every problem with data analytics tools, can you? Well, maybe not with its traditional forms, but the advanced ones, like Big Data Analytics, sure can do the trick.

Utilizing Big Data Analytics tools helps companies analyze all kinds of data patterns, thus minimizing losses, increasing profits, and stabilizing their workflow environment. “Isn’t that just using data to plan ahead?” I hear you say. And well, not exactly! It is, in fact, going beyond planning and heading toward predictive analytics.

A lot of the predictive models on the market are built to aid companies with their risk management and help them solve various dilemmas preemptively. Things like inventory replenishment and management, route optimizations and delay prevention, investment risk assessments, and more. Furthermore, using Big Data Analytics can provide you with better insights into your competition, keeping you ahead of the game at every step of the way.

Why is Big Data Analytics Important?

So, by now, you should be able to see the importance of Big Data Analytics – an integral part of all modern businesses that helps them produce better and more accurate predictions and results. And many enterprises do see this concept as a way to optimize their operations, satisfy their clients, and reap great profits along the way.

We know all of this sounds like a sci-fi premise created to justify a robot uprising. Still, it’s this important form of advanced analytics that has benefited just about every industry across the world. The risk mitigation, cost reduction, and time-saving aspects alone are worth researching and considering Big Data Analytics. But let’s not dwell on the benefits any longer and start convincing you with some actual examples.

Use Cases and Examples

Earlier, we covered how Big Data Analytics is used to help companies in the Entertainment industry get their customers’ preferences right, thus maintaining greater user retention. Well, there’s a similar process going on in the Retail industry as well. The constant and gradual reliance on technology has boosted shoppers’ expectations to such a point that a Retail business would quickly become extinct without any Big Data Analytics tools.

That might sound a bit grim, but it’s just the reality of the situation – everyone values their time. So, if there’s a way to get the results you need quickly, you will take it, regardless if you’re a business owner, a platform user, or a customer. You may be surprised, but this also applies to institutions in the Education industry. There Big Data Analytics is used to identify difficult-to-grasp subjects, understand the strengths and weaknesses of specific students, and even develop personalized learning strategies.

These kinds of personal assessment tools are quite useful and necessary to boost the institution’s success rate and credibility. And what other industry benefits from similar techniques? That’s right, the Health Care industry! By analyzing and organizing all the patient records, doctors can extract some really beneficial insights that can help prioritize patients with more dire symptoms and improve the quality of diagnoses and treatments applied to them.

And since we’re on the topic of medical and clinical enhancements, we can’t skip the utility of Big Data Analytics in the Life Sciences industry. With all the research being done there usually being slow and expansive, advanced analytics help companies in this field optimize their process speed and efficiency at every step of the way. Additionally, they’re able to easily keep track of the status and stage of all their ongoing research, thus always having clear action points.

When a product is successfully researched and developed, it needs to be mass-produced, and as it just so happens, the Manufacturing industry also benefits a lot from Big Data Analytics. For the manufacturing stages to go as smoothly and cost-efficiently as possible, companies have relied on the essential guidance of this approach for years. It helps businesses optimally solve problems like supply chain issues, equipment breakdowns, and workforce constraints.

There are plenty of other industries and examples we can list, but in that case, we’ll be here for a while. So, let us instead go through something more beneficial for you readers – the Big Data Analytics tools and platforms that can help your business organization reach the competitive heights we’ve been talking about so far.

Big Data Analytics Tools and Platforms

Remember the five Vs from our definition earlier? Well, a Big Data Analytics platform needs to be capable of accommodating all those core attributes. The process of picking the right platform isn’t just narrowed down to finding the best data visualization software; rather, it needs to offer scalability and ETL (extract-transform-load) features.

So, what kind of tools should you be looking for in a platform? Well, the list could get quite expansive, but here are some of the top ones to look out for:

Cloud Computing

The cloud provides some much-needed foundations for those key features we discussed, as it’s easy to scale and offers quick and responsive service delivery. In fact, because most cloud computing providers are subscription-based, it makes this the perfect option for all businesses and all industries, as they don’t need to invest heavily in servers and other hardware.

Data Warehouse

The point of a data warehouse is to store all those large amounts of collected data from various sources so that it’s accessible at any time by any department. Usually, there are also some rules in place to show specific departments only the data relevant to them in order to avoid mishandling and foul play. When utilizing a data warehouse, it’s essential to also have established processes to build and maintain a certain level of data quality.

Data Mining

This tool helps users go through large amounts of data and discover hidden patterns, relationships, and insights that can be used to help make those difficult data-backed decisions. From the term itself, it’s easy to get confused and think it extracts data, but it’s, in fact, just a form of data processing. That’s not to say that it is simple, as it’s often utilized with machine learning for more long-lasting analysis techniques.

Machine Learning Algorithms (MLA)

Speaking of machine learning, it’s also a handy and often necessary tool in Big Data Analysis. And while data mining needs machine learning to function more efficiently, there are other ways that MLA can be utilized as well. It all depends on the type of algorithm (supervised, semi-supervised, unsupervised or reinforcement) and the amount of time the business wishes to invest in it.

Predictive Analytics

Finally, when talking about Big Data Analytics, we can’t skip the importance of predictive analytics; after all, we’ve already mentioned it several times throughout this article. This tool uses the whole bag of tricks – historical and current data, statistical algorithms, and various machine learning techniques. This way, they can make assessments for future outcomes and guide your company to make the most optimal decisions at any given point.

Alright then, we now know what tools to look for in a platform. Now you’ll need to actually find a platform that suits your business needs, and depending on what you want to get out of Big Data Analytics, the answer may vary. After all, the concept is so broad that a single tool may struggle to cover all of its requirements. So, here are a few noteworthy mentions:

The Big Three – Qlik, Tableau, Power BI

We’re, of course, referring to the top BI platforms on the market – Qlik Sense, Salesforce Tableau, and Microsoft Power BI. We’ve already made an in-depth comparison of the three platforms, but all you need to know is that they’re all fit to get your business through the Big Data Analytics door, so to speak. They all allow you to effortlessly integrate, explore, and analyze your data through their easy-to-use interface, and their data visualization capabilities are ideal for all your analyses and reporting needs.

Sisense

Another platform worth looking into is the BI platform Sisense. It is thanks to its signature In-Chip Technology that it is able to give users great features like fast data processing, built-in machine learning models, embedded apps and dashboards, and much more. Even though it’s not yet on the level of the Big Three, its steady development may lead it amongst them quite soon.

Snowflake

Suppose you already have a platform to do your data analyses. In that case, you may be interested in a data warehouse platform specifically built to harness the power of Big Data Analytics. Well, Snowflake is just that! It runs atop widely used cloud infrastructures like AWS, Google Cloud, and Microsoft Azure, and with its SQL query engine, it can easily be used for storage, analysis, and processing.

Conclusion

And there you have it – our complete guide on Big Data Analytics! So, if you’re looking for a way to stay ahead of your competition, look no further. This technology can provide your business with insights that will help it improve its products and services and better understand its clients. And if any questions have arisen throughout this article, feel free to contact us, and we’ll be happy to answer them for you. Also, be sure to schedule a consultation with us if you wish to find out more about how your company can succeed in today’s fast-paced world.

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