5 trends that define the next shift in Data Intelligence
By Kamal Jacob
Let’s have a look at the graph from Google Trends (05-2014 to 05-2019). It reveals an interesting fact that five years back, the term “Data Science” was almost unknown. But, on the other hand, the vast changes prevailing in today’s technological landscape has changed the whole picture.
The role of Data science, Big Data, and Data Analytics, which collectively can be termed as Data Intelligence, has been elevated to many folds in almost every industry, whether big or small because extracting value from collected information has proven to be invaluable for business. This is the reason, the trends in data intelligence are also changing from a departmental approach to business-driven data approach. In this competitive era for business, to stay ahead in the competition, organizations need to implement the right data-driven Data Intelligence trend.
If we see Data Intelligence trends in the last couple of years, they are mainly revolving around some big names like Artificial Intelligence, Machine Learning, along with some newer technologies like Blockchain, Serverless Computing, and Digital Twins. Although, all these technologies are doing remarkably well, whenever it comes to the future of Data Intelligence, the prediction of the co-founder and CEO of Kaggle, Anthony Goldbloom, comes in mind that soon Data Centers are going to be replaced by business-specific data Sciecne terms. What does this mean? This means, for higher efficiency and productivity, the coming years may set the stage for advanced data intelligence techniques to take-over the routine business processes.
To take it a step further even, in this article, we are going to discuss 5 trends that define the next shift in Data Intelligence. Curious to know! So, let’s get started.
1. Quantum Computing: According to DOMO’s Data Never Sleeps 6.0 report, “Over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7 MB of data will be created every second for every person on earth.”
As the complexity and size of our data set balloon are growing day by day, we need really a fast way to process, organize and extract value from this data. The search stops at Quantum Computing.
By using ‘qubits’ for storing information, instead of 1 or 0 used in classical computing, QC will be able to complete complex calculations in mere seconds, cut processing time immensely. It gives companies the opportunity to make a timely decision to achieve more desired results. Isn’t it?
Despite being in its infancy, some big tech giants like IBM, Google, Microsoft, D-Wave best positioned for a quantum leap in quantum computing.
1) In 2017, IBM simulated chemistry with quantum computing with the record-breaking simulation of the BeH2 molecule. Recently IBM launched the world’s first integrated Quantum computing system.
2) Google’s quantum power surpasses that of IBM and builds Bristlecone, 72-qubit quantum chip, suggesting that their quantum supremacy is around the corner.
3) D-Wave Systems, the only company producing and selling commercial quantum computers, builds D-Wave 2X. Currently, D-Wave has the largest claimed number of qubits in its processor at 2048 qubits.
4) In the race of quantum computing, Microsoft is not far behind and launched Q# the quantum development kit.
For sure, Quantum Computing is defining the next shift in Data Intelligence and is enabling organizations to optimize large chunks of unstructured data for all types of use cases and portfolio analyses.
2. Fast growing IoT Networks: IoT (Internet of Things) are becoming quite common and influencing our lifestyle from the way we react to the way we behave. The home appliances we can control with our smartphone, the smart cars providing the best route or the smartwatch which is tracking our daily activities, thanks to IoT for all this. The growing craze for IoT is drawing more and more companies to invest in this technology.
IoT, a giant network with all the connected devices, where these connected devices gather and share data about how they are used and in which environment they are operated. This results in a vast amount of data which need to be managed and analyzed in a manner to get valuable insight into consumer behavior. In the near future, organizations will jump on the opportunity to provide better IoT solutions.
3. Edge Computing: For almost every sector, the vast volume of data, produced by various sources, represents treasure troves of actionable information. But with the increase in data volume and velocity, inefficiency to transmit all this information to a cloud or data center also increases. What if we put applications and data closer to the users or “things” that need them—that’s where Edge Computing plays an important role. Edge data centers deliver several key advantages like higher bandwidth, lower latency, regulatory compliance around location and data privacy.
IoT and edge computing seem well made for each other. As per the estimates, by 2020 the total number of connected devices are going to be staggering 26 billion in number. As of now, the cloud is the only solution taking care of storage, analysis, and numerous other stuff. But the flood of information from these massive number of new devices can impede the whole cloud operation. Do we need to worry? NO, with the advent of modern science and technology, “Edge Computing” is the solution. In fact, IDC research predicts, in the next three years almost 6 billion devices will be connected to the edge computing solution and around 45% of the IoT created data will be stored, processed and analyzed at the edge or close to the network.
When the talk is about disruptive technologies, the name of big tech giants like Microsoft, Google, Amazon will invariably come. These companies are the frontrunners in this case for promoting the next generation breakthrough Edge and IoT technology.
1) Microsoft’s product Azure IoT has already bagged second place and they recently launched Windows 10 IoT core also.
2) In recent years, Amazon has also ramped up by investing aggressively in IoT. Amazon’s AWS IoT is the latest innovation from this tech giant.
3) Google’s self-driving car technology and Kittyhawk are the finest examples of real-time disruptive IoT applications.
4) Other than these tech giants, GE Digital is also using Edge computing and Edge capabilities in their digital wind farms.
4. Predictive Analysis: The use of analytics tools to process the data and determine the reason why certain events happen, remains the key strategy for businesses to have a competitive edge. But, what if companies can peep into the future and predict consumer’s next action before they even do it? Yes, predictive analysis, a sub-field of Data Analytics and Business Intelligence, makes it possible. PA, combining the power of Data Mining, Data Modeling, Data science, Artificial Intelligence, and Machine Learning, deals with an in-depth analysis of past events and forecasts in future events.
Predictive marketing that extends well beyond the marketing department, is the next shift in the marketing and advertising sphere. It requires the Integration between marketing executives and technology specialist. Organizations that develop and leverage PA capabilities will have an advantage in this competitive era.
5. Social Media:We’re all connected, all the time, it’s the biggest impact of social media on our lives. In this globalized village, it is Earth’s biggest focus group. Isn’t it? But, if you are wondering how social media defines the next shift in Data Intelligence, think about the enormous data, 2.77 billion active users (increasing day by day) are generating through various social media platforms like Facebook, Instagram, YouTube, Twitter, etc.
We post our emotions, thoughts, and opinions on social media platforms, giving unprecedented levels of insight that directly affect company strategy. Whenever there's a slight or massive change or upgrade in social media features, it results in: viral campaigns, new advertising ideas from brands, benefits to brands, benefit to the audience, etc. This is going to be the age of dynamism where data will never be static yet will be in huge demand for the audience insights it provides.
In the form of social media marketing, an incredibly fascinating battle for the heart of eCommerce lies ahead. How? Let’s have a look at the two examples below:
6) Virtual Spaces: The future of marketing belongs to “Virtual Spaces”, where virtual reality and social media converge. Facebook provided a glimpse of it in 2017. With the immersive AR experiences, companies invite people out of their filter bubble. Would you want to “test drive” your favorite car from the comfort of your home? Of course, Yes!
7) Smart Speakers: A profound development for marketers is products like Alexa, Google Home, Cortana, Siri. We can say them, Smart Speakers because when we ask them to find an answer, we don’t get the list of videos, research reports or articles, we get the ANSWER.
And that’s a wrap! Hope this blog post proves to be insightful for you! Share your thoughts in the comment section and we would be glad to read them. Looking up to building a career in Data Science? Explore our Data Science courses here to upskill in data science.