What to Expect in Data Science and Big Data in 2018
Big data, predictive analytics, and machine learning have all become buzzwords in the last few years. As 2017 comes to a close, let’s take a look at the trends that will continue to shape the information landscape in the years to come and which ideas will lose traction.
1. Increase in the use of Hadoop & Spark
To support the increasing demand for Big Data usage, more companies will start learning about these tools and using them to make sense of the information gathered from sensors, transactions and even CCTV.
Since most organizations are looking for an actionable, real-time answer, in-memory analytics tools like Spark will receive even more attention. The significant advantage is that analysts are no longer restricted to data samples and can even play with techniques and as many iterations as necessary to get the correct model. The impact on speed is tremendous, up to 100 times faster than regular Hadoop.
2. Self-disruption
Reinventing the offer is sometimes the only way to remain relevant. The natural life-cycle of each product or service is accelerated by technological advancements and even successful products like Amazon’s website are expected to be replaced. For example, a prediction by Gartner foresees that brands will redesign their sites for visual and voice search to increase sales up to 30%. This change is triggered by the rising importance of mobile and app-based browsing which have surpassed and will almost replace desktop versions. A recent example includes Apple’s Face ID for iPhones, which replaces their previous trademark Touch ID.
3. Clean up data lakes
Amassing information in the cloud does not make it a data lake, but a data swamp, that produces no real value to the organization. The key is to increase the impact of the information on the enterprise by making it easily accessible through self-service and governed by precise rules. This approach is scary for companies that have only kept their data in departmental silos, but it is a viable approach that reduces redundancy and creates a premise for synergy. To clean the data lake, the information must be categorized, and metadata added or each initiative to analyze the data will have to start from scratch.
4. Increase security and governance through AI
Since the time of the ARPANET, security has been a primary concern of online communications, and with the expansion of IoT, it is becoming an area that demands rapid advancements to match the hackers’ attacks. The best way to detect anomalies is to use machine learning to identify patterns that could signal a malicious activity on the respective channel. ISPs are responsible for securing communication on their end, therefore, we can expect a more proactive role on their part. The introduction of more rules and standards for wearables and other IoT are also possible next year.
5. Increase the importance of real-time machine learning
If software development has been at the core of technological advancements so far, that means now non-supervised machine learning is the new fuel. Data science consulting firm InData Labs advocates for the use of real-time stream processing systems that are ready to scan through semi-structured or unstructured data. Having on the spot answers increases the speed of decision making.
6. Develop more blockchain apps
The interest in the underlying technology of Bitcoin has risen by 400%, and it will continue to do so next year, first for the banking industry and slowly getting into other sectors. Possible applications include tracking a product up to the producers of the raw materials, securing data and revolutionizing the payment system by removing current banking and currency exchange fees. Judging by the range of possible applications, significant players in the industry are expected to introduce blockchain-as-a-service to complement their cloud products and bring this technology to the mainstream.
7. IoT- Ask Siri for a coffee
In 2018, we can expect an expansion of Big Data platforms such as Azure and AWS and the introduction of new connected devices, both in B2C and B2B segments. There is an intense hype related to IoT in the predictive maintenance industry with powerful applications in the automotive industry. We have hope this will be the year of the safe self-driving car. The estimations show that the number of devices will be around 12 billion and is expected to grow to a staggering 46 billion by 2021. We can expect smart tools to become even smarter and interconnected, for example asking Alexa or Siri for a coffee, brewed by a linked device.
8. New hot jobs and not enough qualified people
As the demand for Data Specialists continues to rise, the number and types of jobs in this sector will multiply almost exponentially. A trend highlighted by DataStax for last year is still valid, and we can expect growth in the number of data engineers instead of data scientists. As there is more data to be handled and analyzed, the need for structure is on the rise. Problems are becoming less exploratory and more task-oriented. The estimates show that there will be a deficiency between the demand for qualified personnel and the number of people with the required skills.
9. Investment in Data Science companies will increase
Data Science companies are the new gold rush, and venture capitalists are eager to invest in the next big idea. The projected growth is expected to attract even more funding. Applications in main business sectors like finance, healthcare, retail, and transportation ensure investors that there is potential.
10. Data is the latest product
The interest of investors is sparked by the fact that information is no longer just a helpful resource, but is becoming a product itself. It will soon be regarded as a valuable piece of intangible capital, which is, in fact, true since information is the corner-stone of know-how, an essential part of intangibles. We can expect new business models to emerge around selling and analyzing data.
Apart from these trends, the development of data science will also be linked to better personalization, growth of conversational interfaces (chatbots) and the focus will shift from idea to ROI.
