The pros and cons of big data

In 2018, businesses have more data at their disposal than ever before, with an estimated 2.5 quintillion bytes created everyday. But interpreting the insights it offers can be an arduous task if you don’t have the right analytical process in place.

As with any new technology, there will be teething problems. The implementation process may not go entirely to plan, or the results obtained from the data may not comfortably align with your business objectives.

When implementing big data protocols in a business, it’s crucial you remember that big data doesn’t mean you have lots of information. The term comprises all of the processes and tools that are used by a company to analyse and utilise large complex datasets.

If you’re looking to add a big data solution to your day-to-day business operations, here are the benefits and challenges big data can bring to your organisation.

It helps you structure incoming data

The first, and arguably the most important, factor to consider is that analytics can help to structure your existing company data. As a business, you will acquire information from numerous data streams, many of which will be—to put it kindly—unorganised.

Implementing a big data solution should allow you to add structure to data before placing it in a storage silo. These processes will offer faster access to information when it’s needed, which should speed up your business decision-making process.

Meticulously structuring data can also unearth new patterns, which will lead your business to answer questions you weren’t aware you needed to solve. Don’t worry, this is a good thing.

It can keep your other data safe

Protecting data against security threats should be high on your list of priorities, with 1 in 4 businesses at risk of experiencing a data breach. As your company begins to collect more data, it’s important to recognise the heightened risk of a breach from both internal and external sources.

When using data analytics, protection against these threats is exponentially increased. Deploying specific analytical techniques allows for immediate real-time verification and secure storage of data. By following these protocols to the letter, your business can determine if a security issue has occurred. Then, by using new information that’s undergone similar instantaneous analysis, you’re able to investigate and eradicate the threat.

Data helps you gain a market advantage

Understanding your market in order to gain an edge over competitors is essential in any business—but it’s especially important if your organisation operates in sectors like retail and manufacturing.

Using data you’ll be able to track a customer journey all the way down the funnel to the point of sale. The detailed information held on a customer can also help you identify which product a particular customer favours, where cart abandonment occurs, and what offers are likely to lead to a conversion.

Data held on your products can help automate which products to restock, what to remove from production, and which to bring back into circulation.

It builds trust with clients

The risk of potential security threats often overshadows the implementation of big data, particularly in the financial sector. However, by administering new analytic techniques to protect customers’ privacy, big data can provide an extra layer of security and build consumer trust.

By using specially designed analytical protocols, your business can identify the smallest discrepancy in a customer’s account. This recognition can lead to early detection of fraudulent activity, and the prevention of a full-scale attack.

Analysing big data in your business

In finance, the relationship with your customers and clients centres around trust.

“The use of big data comes from better understanding your client needs, and being able to prepare them for environmental changes that may affect them,” says Bob Katz, CEO of the Financial Analysis and Control Technology Service. “Providing proactive advice to clients of possible risks impacting their financial objectives due to external events is extremely valuable and enhances that relationship.”

This added layer of security will help affirm the relationship between you and your clients. So it’s also crucial to keep security protocols up to date when working with big data.

Visualising data can become difficult 

The goal of an analytical procedure is to convert collected data into a format which is more readable. This conversion process becomes more difficult when procuring large amounts of data as, often due to the sheer volume, it becomes difficult to decipher which pieces you need.

“We often say, all data is interesting, very little of it is useful. We could easily report hundreds of pages of ‘interesting’ findings to our clients, perhaps only 1-2 paragraphs of which is useful and actionable for them today,” says Sam Underwood, VP of Business Strategy at data analytics consultancy Futurety.

“This is where the real work comes in, deciding which findings are potentially business changing, and which are just good to know.”

The speed of collection is often too fast

As your business grows, it’s logical that you will create more data. Your data will need to undergo strict analysis, and it’s at this point where issues arise.

If the necessary protocols—such as pre-programmed data models or a specially designed algorithm—aren’t in place at the start of data collection, the influx of data streams can hinder the entire process and lead to delays in other areas of the business.

The challenge of knowing which data is important—and how to use it

Implementing new technology can certainly add profitability to your business in the short term,—but it’s crucial that you understand the full value of your data in the long run, as according to Qotient, this could lead to potential 20% increase in profit. It’s often the case that businesses are unaware of the power they can unearth by performing a complete analysis of all their data.

When you first begin the analysis process, it can be difficult for your company to decide which aspects of data are the most important. Although you may feel that monitoring the performance of a particular product is vital, it may not result in the best findings, so your business strategy will need to change to accommodate these insights.

The use of big data in healthcare

Once you’ve identified which data is valuable, the next hurdle your business will face is figuring out what to do with it.

Most organisations have various data streams that offer insight across many different channels. The most significant challenge faced in big data is that people don’t know how to use it. “For years, people bought big data products, hyped in airports around the globe, and did nothing with them. Or, they’d spend months implementing a solution, only to pull the plug after that big data solution couldn’t perform,” says Jason Wisdom, CTO of Aponia Data.

Big data is not one-size-fits-all. It’s a tool that works great in specific situations and doesn’t help at all for others. “I have seen big data try and replace a retailer’s Point-of-Sale system,” says Jason. “To nobody’s surprise who knew big data, the new solution was much slower than the old system.”

Slow adoption in specific sectors

Although big data adoption is on the rise, with 53% of EMEA businesses now harnessing the technology, some sectors are yet to embrace its power entirely.

The healthcare industry is often on the back foot when it comes to new technology, with SAS reporting that only 36% of UK establishments take full advantage of analytics. Dr. David Talby, the Chief Technical Officer of Pacific AI, believes there are two leading causes, “First is the heightened requirement for data privacy compliance, which reduces data sharing, and hacking-style solutions that speed up progress in other verticals,” says David.

“Second is the heightened need to explain models. No doctor will diagnose or treat a patient differently just because ‘the computer said so.’ The human-computer interaction issue of how to get clinicians and AI’s together is still very much an open problem.”

Whether your business is looking to implement a new analytical system, or you’ve recently added big data as part of your business strategy, you may face an uphill battle to get buy-in during the first stages of implementation. However, when implemented correctly, you will receive a healthy ROI and increased operational productivity.

What challenges have you faced when introducing big data analytics into your business? Let us know in the comments below.

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