Big Data Reviewed: Top Trends and Reasons to Implement It

We’ve all heard a term some may find intimidating: Big Data. I began my research bearing that in mind but later realized that I was wrong. It’s been used in the past months for things like predicting COVID-19 disease spread, finding new treatments, and even planning clinical management during the global health crisis. Big Data allowed for a quicker and proactive response to the pandemic, but that is only one way in which it has proven to be such a great investment. If you want to find out ways in which this technology can bring value to your company and how to find the right partner for it, please continue reading.  

Let me go back and give you a more appropriate definition, Big Data is defined as a quantity of data, that is large in size and exponentially increases its 3 Vs, or variables,: Velocity, Variety, and Volume. Nowadays, there are plenty more Vs, like Volume, Velocity, Variety, Variability, Veracity, Visualization, and Value, but the first 3 are the essential ones. 

This data is generally complicated to stock, investigate & transform into insights with traditional analytics tools. Furthermore, Big Data Technologies are products that incorporate data mining, storage, sharing, and visualization. Recently Advanced Analytics have been incorporated, they include Predictive and Prescriptive analytics. The former one predicts what probably will happen. The latter tells you what you need to do to make things happen. In general, Big Data Technologies include everything from tools to frameworks, and techniques used to analyze and transform data.  

Now that you know what Big Data is, you must be wondering why it has become so popular in recent times. Currently, this technology is one of the most demanded in the category of enterprise software, because of the fast and constant growth of information volume collected by companies. Big Data applications help process these large amounts of data because they have special frameworks created to implement and support their functions. They are different from traditional data or analytics apps because they actually allow the rapid processing and structuring of these big quantities of information, in real time.  

Big Data is growing at such a high rate that by 2024, 75% of companies will increase at least 5 times their data analytics infrastructure. Another pretty impressive figure is that at least 33% of companies will have analytics for decision intelligence. With help from Big Data, this framework allows company leaders to design, execute, monitor, and adapt decision models. It’s no wonder that most successful companies worldwide either already have, or are looking for an efficient Big Data solution, proof of it is that Netflix saves around $1 billion dollars a year retaining customers by leveraging their data. Meanwhile, the US economy loses more than $3 trillion dollars a year because of poor data quality and data misuse.  

Here are a few of the main benefits of Big Data implementation:

• Improved business efficiency 
• More effective Research and Development  
• Faster innovation cycles  
• Smoother business process adjustments  

Now that you’re interested in Big Data you may be wondering, is it easy to implement? Will it be extremely expensive? Will it be difficult to integrate it into my existing ecosystem? Thankfully, Data as a Service (DaaS) exists, which allows you to acquire a Big Data solution that is cost-effective, has simplified access, and is easy to update. Need more proof that DaaS is necessary? 90% of companies worldwide are using it and generating revenue. Retailers are claiming that they’ve experienced up to 60% increased margins after implementation, while Oil & Gas companies reduced operational costs up to 40%, plus they’re reducing risk exposure.  

Big Data can also have pitfalls like limited storage options, distributed frameworks, cybersecurity issues, and unreliable providers. That’s why finding the right DaaS partner is so important. According to the Harvard Business Review, some things you should expect your vendor to do before developing a solution are:  

• Finding specific issues to solve within your company  
• Having a practical understanding of your business model 
• Reviewing all legacy applications  
• Committing to having enough developers to source an appropriate Big Data team  

It’s essential especially that your partner can provide appropriate consulting to identify business problems that are strictly defined, easily addressed and that when solved with the help of Big Data, will bring value to the company. On another note, it is mandatory to ensure data privacy and create a strategy that is aligned with all the regulations. This leads us to a Data environment that needs to be governed, architectured, and exploited to generate enterprise benefits through its strategy and objectives. Everything must be aligned with the enterprise strategy to ensure the right value generation. 

Thankfully at TEAM we have 20+ years of experience with data projects and an approach we’ve perfected over the years. We have developers who are experts in data analytics services and are available to help you with the complete implementation process, starting with providing a roadmap through project deployment. We collect, structure, understand, and leverage your organization’s quality data to fuel innovation, cut costs, and drive revenue. 

It’s also key that your providers are innovative and up to date on Big Data trends, have experience with them, and are able to create solutions that include these. According to Gartner, some trends you’ll find are:  

• Augmented Data Management: Allows companies to easily identify what data they have, what it means, how it delivers value, and whether it can be trusted. Utilizing the statistics of existing systems and their available capacity and known resources policy-level instructions will determine where data operations will take place.  
• X Analytics: Big data for structured and unstructured content which helps increase augmented data management automation in redundant tasks.  
• Blockchain: Provides the full lineage of assets and transactional data. Allows transparency for complex networks of participants.  
• Graph Analytics: Facilitate rapid contextualization and decision making. Allow the exploration of relationships between organizations-people-transactions. Uncover hidden patterns.  
• Location Analytics: Location analytics extracts additional insights from business data by adding a layer of geolocation information. Usually, this is used for transactional data such as sales, logistics, and supply chains to allow a new dimension that helps contextualize specific figures. 

After reviewing what Big Data means, and how it can improve your company on many levels, the fact is that having a great provider is only half of the work a company must do in order to have a successful implementation strategy. In accordance with the Harvard Business Review, Big Data, “…will unearth efficiencies and misconceptions that complicate leadership and disrupt conventional thinking.” With that being said, organizations must have an open mind when it comes to implementing this technology and understand that revealing the issues within a company will only make them much more successful in the end.  

My messages are always open if you want to discuss this specific topic or any other. If you’d like us to set up a virtual coffee break, I'd be more than happy to meet you. For more interesting content head over to our company blog. Wishing you plenty of safety and health!