Big Data: What it is and How it’s Used

The IT sector is continuously evolving and, along with that, Big Data is rapidly growing. You may have a basic grasp of Big Data or at least know what people are talking about when they use the term. Broadly defined, Big Data refers to large data sets that can reveal trends, associations, patterns and relationships between human behavior and interaction.

If you want to understand why Big Data is vital for businesses and how it influences the growth of the IT industry, here’s what you need to know.

How is Big Data used?

Understanding trends in human behavior is key to building a strong business. When companies understand their clients’ needs and desires, they can produce successful content, advertisements, products and business strategies centered on that information. That’s where Big Data comes in.

From Facebook “likes” to purchase history to website views, everything we do online is stored in a massive collection of data, which is largely referred to as “Big Data.”  While there are many definitions circulating the internet, Big Data is collectively known as information that can only be deciphered and analyzed by computers, because there are so many statistics to crunch.

Examining the Four (or Five) V’s of Big Data

Whether it’s in a podcast or article online, you’ll often hear about the four V’s of Big Data: volume, velocity, variety and veracity. These four terms help break down all that Big Data encompasses.

IBM explains the terms:

1)      Volume is the scale of data. An estimated 2.3 trillion gigabytes of data are created each day.

2)      Velocity is the analysis of streaming data. In other words, velocity is the growing speed at which data arrives at various organizations, according to Forbes. Today, data comes in as a constant flow, which some attribute to the increased use of mobile devices and social sites.

3)      Variety refers to the different forms of data. Information stored at healthcare facilities, stats from wearable health monitors, Facebook posts, YouTube videos and tweets are all examples of data forms.

4)      Veracity is the uncertainty of Big Data. This fourth V is not acknowledged by every business, yet it draws attention to the trustworthiness of data. IBM states that one in three business leaders do not trust data for decision making, which is why many organizations are focusing on improving data quality.

IBM notes that Big Data is “the ability to achieve greater value through insights from superior analytics,” and states that a fifth V to be considered is Value.

Why is Big Data important for your career?

To ensure they keep a competitive edge, businesses rely on data and analytics to make decisions. But when information is gathered and computers utilized to compute the data, companies need to know what to do with all that material. Accordingly, more IT professionals with data science skills are needed in the workforce. Trained professionals will take the data processed by computers and draw meaningful insights from it. Companies can then make business decisions based on those findings.

To stay relevant in an industry that is always evolving, IT professionals will need specialized training and education in Big Data analytics to keep current with the trends.

IBM recently predicted that data science skills will not be only recommended for IT professionals, but that it will also be required in order for them to be employable and successful. In today’s workforce, most employers want to hire IT professionals who have knowledge and training in this area, because Big Data is rapidly growing in volume and importance.

Big Data Trends to Watch

As Big Data continues to grow, increasing numbers of jobs will be created so that businesses can compute all this information. What skills will employers be looking for? IBM expects that “people who can design AI-powered products that combine robotics, embodied cognition, IoT (internet of things) fog computing, deep learning, predictive analytics, emotion analytics, geospatial contextualization, conversational engagement and wearable form factors will be in hot demand.”

Information Management predicts that more mainstream organizations and previously skeptical businesses will embrace Big Data and IoT. Data blending also will be a new trend, as companies start to combine information such as social media, mobile apps, CRM records and purchase histories to draw conclusions and make business decisions.

Here are five trends to watch, according to Information Management:

1)      The Internet of Things (IoT). Businesses are looking for more ways to connect things (coffee makers, washing machines, refrigerators, lamps, etc.) with the internet in order to track more data.

2)      Deep Learning. The use of machine learning techniques and algorithms is still being developed but shows great potential for helping businesses overcome obstacles and will likely be used more in the future. Deep learning delves into the world of artificial intelligence.

3)      In-Memory Analytics. This technology takes information loaded into RAM which can accelerate analytical performance and reduce disk I/O bottlenecks.

4)      Cloud Systems. Information Management expects a “convergence of data storage and analytics, resulting in new, smarter storage systems that will be optimized for storing, managing and sorting massive petabytes of data sets.” The cloud-based Big Data ecosystem is expected to grow rapidly in the business sector.

5)      Apache Spark. This trend is one to keep an eye on; according to Information Management, the “Apache Spark project provides Spark Streaming to handle processing in near real time through a mostly in-memory, micro-batching approach.” This processing tool has become a new favorite among many organizations.

Successful businesses know how to gather, analyze and utilize data analytics, and if companies aren’t continuously innovating and relying on data for decisions, they will soon go out of business, as Information Management notes. Accordingly, IT professionals will need to continue learning and training in order to be relevant in this world of Big Data.


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