Whether or not you realize or consent to it, big data can affect you and the way you live your life. Many find the buzzword as a pure blessing while others curse. Well, I personally feel that it is somewhere in between; it can contribute to both the insight and the fog of visibility. In the following post, I’m going to cut right to the chase and shed light on a few of the fantastic things that Big Data makes possible in the upcoming years.
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Whether or not you realize or consent to it, big data can affect you and the way you live your life. Many find the buzzword as a pure blessing while others curse. Well, I personally feel that it is somewhere in between; it can contribute to both the insight and the fog of visibility. In the following post, I’m going to cut right to the chase and shed light on a few of the fantastic things that Big Data makes possible in the upcoming years.
With the emergence of big data technology, businesses can make ground-breaking insights available in the real-time. And not only businesses but even . Whether you search on Google or social networking sites like Facebook, data can be derived from any source. With the advent of smartwatches, glasses and even smart clothes, we have started creating a world featuring high data collection mechanism. Unfortunately, many of you are found discouraging such potential of course because they fail to understand its capabilities.
According to IDC, Big Data revenues are estimated to cross $187 billion in 2019. It is said that the amount of data in the world doubles every two years, and by 2020, the digital universe will reach 44 zettabytes or 4 trillion gigabytes in data. In fact, banking and manufacturing are the ones who invest heavily in big data these days. As a result, it is being touted as the “definitive source of competitive advantage” across industries.
Where is Big Data Today?
Speaking of the data universe, around 2.7 Zettabytes of data exists till date. Hard to believe, isn’t it?
Approximately to conduct more and bigger data research projects.
Facebook stores, accesses and analyzes 30+ Petabytes of user-generated data.
By 2020 it is assumed that business transactions whether it is business to business or business to the consumer will reach 450 billion a day.
If we seek globally, around 5 billion people are found calling, texting, tweeting and browsing on mobile phones.
Walmart handles more than 1 million customer transactions every hour, and this is not it! This particular data is imported into databases where already you will find 2.5 petabytes of data.
A few years ago, decoding the human genome took ten years, but now it can be achieved in a week- nothing more/ nothing less.
94% of Hadoop users perform analytics on large volumes of data. However it was not possible before; 88% analyze data in greater detail, and 82% can now retain more of their data.
Every minute of the day a new video is uploaded on YouTube.
Data production will be 44 times greater in 2020 than it was in 2009
What the future holds?
Down below I would like to mention a few facts to take into account about big data market growth.
Widespread adoption
More and more companies are seen leveraging the and put those findings into “active use.” Apache Hadoop/ Hive, Apache Spark, and Presto, are some of the most popular engines used to accommodate data preparations, machine learning techniques, reporting and analysis workloads.
Increasing volume of commands
Again speaking about Apache Hadoop/Hive, Apache Spark, and Presto, the total usage across these engines has grown by 162%. Being known as one of the fastest growing engines, users are experiencing a 420 percent growth in compute hours and 365 percent expansion in total number of commands run.
Get acquainted with new tools
In addition to top-three engines, around 30 percent of organizations have started using these tools. For example- Apache Airflow, it is used to analyze sophisticated data preparation pipelines and operationalizing machine learning using Python code. In simple words, monitoring of jobs, handling failures and the list goes on. Apart from this, you can even think of considering tools like XGBoost (predictive machine learning tool), Pandas (Python-based data science tool used for statistical analysis) and MLLib (Apache Spark’s ML library) are also gaining in acceptance.
Productivity has increased
While usage and implementation grow, data-driven organizations are focused on optimizing many users running commands in each engine, such that costs reduce and the process is nearly automated.
Increase in the requirement of Data scientists
but do you think that you stand a chance? Organizations are found focusing on realizing business projects, leveraging the technologies and big data they have and need, to get the results they want, with a clear ROI. In order to drive more revenues, enhance customer experience, save costs, create new business models, find new sources of revenue, etc. It’s your fair chance to prove your value. So, go for it!
_Author Bio:_Charles Richard is a Business Analyst at. and A passionate writer who loves to write that matters and believes that writing is the best media to express what you want to share with the rest of the world. He can be found on Twitter at .