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Data-as-a-Service practices, here are trends we think will be driving the big data technology market in 2020

02 Jan

Businesses have to be solely dependent on the experience of their managers, leaders, and executives for so many years.

However, as technological progress continued, these businesses now have the support of data analytics and insights. 

With the advent of Big Data and its imminent inclusion in myriad forms of industries, it is currently projected as a game-changer for all the corporate issues of the present connected age. However, since most of the hypes often die down, the initial frenzy surrounding the Big Data is slowly subsiding. It is no longer part of the so-called coveted Hype Cycle of reputed analyst firm, Gartner. However, companies haven’t stopped investing in it. Big Data is constantly getting stronger and is definitely poised to make much bigger strides in the deliverance of highly accurate insights. What actually has happened is that big data is currently an established technology that has move over the unnecessary fuss about it. Now, different companies are seeking real value out of Big Data solutions, not simply towering and big promises.

In this regard, DaaS or Data-as-a-Service has appeared at the technological landscape which isn’t anything revolutionary, and most of the people might have encountered it in the form of buying music, image files or videos from different online sources. However, the entry of major players from map right from the product catalog vendors to map data providers completely changes the entire concept. It need not have to be a dedicated SaaS solution that has to get into the market. In case your company has the data which has value for some others or has difficulty in maintaining it, then it is better to sell it per megabyte or by volume quotes.

Having said that, at present, there are a plethora of trends that custom software development services should look forward to which will be driving the big data technology market in 2020. Here are some of them.

1. Inevitable Preparation of a Robust Strategy for Data Governance

In order to use Big Data in a secure and most efficient manner, the businesses need to have a fool-proof and robust governance framework which offers an accurate description of the entire data provenance, effectively manages the data accessibility as well as fosters democratization. The GDPR laws laid down by the European Union will have a monumental impact on exactly how the businesses handle a large volume of data of individuals living in any of the EU member countries. Due to the strict provisions of this regulation, a business that is guilty of malpractice won’t get spared easily. There will be penalties that will run into millions. However, only almost one-fourth of EU companies are compliant with this regulation. The situation is quite bleak, and as long as we consider the future of Big Data, the entire issue of governance will keep its relevance.

2. Leveraging the Hidden Potential of Dark Data

When it comes to Dark Data, it is essentially the digital data that businesses collect every day and keeps it stored, but it is never utilized for any particular purpose other than only the regulatory compliance. As data storage is easier, most of the businesses never leave it out. Old data formats, documents, and files within the companies are simply stored and getting accumulated in vast amounts every second.

Essentially, this unstructured data is quite a goldmine for meaningful insights, given that it is effectively analyzed. Almost 90 percent of the data which the companies store falls under the category of Dark Data. There have been efforts to use this data type and has picked up steam over last year. Hence, in 2020, we will see the inclusion of this Dark Data. The companies have to process all data types in order to extract maximum benefit through the process of data crunching. Asp.net development services can get benefitted the most by developing custom software to crunch this data and gain invaluable insights.

3. Rise of Quantum Computing

About the next computing disruptor, quantum computers are just around the corner. Being among the most powerful computers which are based on the Quantum Mechanics principles, the computers are yet to make an entry within a few years. However, it will certainly push the boundaries of traditional computing and will be able to conduct analytics of unimaginable proportions. Big Data’s predictions are currently incomplete without this computing. Big Data services have to get accustomed to quantum computing to leverage its fullest potential in the years to come.

4. Loss of Significance of Data Lakes

For quite some time, data lakes which are storage repositories that actually store all of the raw data of the companies in their corresponding native formats remained to be a prized possession of these companies. Among the chief selling points of these data lakes is that it actually takes away the most concerning issue of information silos.

However, the issues of consistency, quality as well as lack of alignment with the enterprise teams or even governance of the highest proportion are turning out to be the stumbling blocks to garner actionable insights essentially. Most of the businesses consider these data lakes as among the most challenging and disputable data sources. They should either live up to their promise or give away and fall wayside.

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5. The proliferation of Artificial Intelligence and Machine Learning

These two technologies will certainly gain more power and importance in the coming year. Both of them are the two sturdy and powerful technological workhorses which are constantly working quite hard to transform and deduce meaning from the unwieldy big data into a much approachable stack and better insights.

Deploying both of these technologies will allow the businesses to easily experience the magic of algorithms through different practical applications like customer churn model, pattern recognition, video analytics, fraud detection, dynamic pricing and much more. Companies that are investing heavily in AI are much more optimistic that their revenues will certainly increase multi-fold in the year 2020. Also, these technologies will assist the businesses in prognosticating events with quite unmatched accuracy and precision.

6. Increased Traction of Edge Analytics

The proliferation and massive adoption of the Internet of Things or IoT devices in the phenomenal form actually demands a separate kind of analytics solution. For this, edge analytics is certainly the most befitting answer. It essentially means to conduct real-time data analysis at the network’s edge or point where the entire data is actually captured without even transporting that particular data to a particular centralized data storage.

Due to its on-site nature, it provides benefits like minimization of the entire impact of load spikes, reduction in requirements of bandwidth, reduction in latency as well as great scalability. This opens up new avenues for cloud integration services to provide cloud software solutions to allow edge analytics at the network’s edge. Certainly, edge analytics will find quite a few corporate takers in the near future. The total edge analytics market is set to increase by great proportions. It will certainly have a much noticeable impact on the entire big data analytics too.

7. Emergence of Graph 

Graph databases and graph processing allow data exploration in a certain way that most of the people actually think which reveals relationships between various logical concepts as well as entities like people, organizations, transactions. It is predicted that graph processing, as well as graph databases, will grow by substantial marking in order to continuously speed up data preparation and even allow adaptive and more complex data science. Essentially graph enables the various emergent semantic graphs along with knowledge networks.

8. Application of Blockchain

It is one of the trends which goes beyond data as well as for analytics. It is essentially about cryptographically providing support to immutability across a complex network of trusted participants. Also, it tracks in case something has changed, so from the perspective of data, blockchain can be quite useful in tracking things such as deep fakes or the infamous fake news. Big Data services have to invest in bringing blockchain within their solutions heavily.

9. Introduction of Continuous Intelligence

It is about enabling much smarter decisions via advanced analytics and real-time data. It encapsulates situational awareness and suggests the action be taken. It is quite intelligent, outcome-focused, and automated. In the years to come, most of the new business systems will certainly incorporate continuous intelligence that utilizes real-time context data in order to improve business decisions. This will certainly revolutionize the way real-time analytics is performed and bring in necessary innovations to aid the businesses.

Read the blog- Types of Challenges and Solutions in Big data

10. Growing space for persistent memory servers

They will enable larger memory along with affordable performance as well as less complex availability. Few database vendors are currently rewriting their own systems in order to provide support to this kind of server that enables the analysis of more volume of data, also in real-time. It will help the businesses to store more data in order to gain actionable insights and make informed decisions.

11. Data Analysis Automation

Traditionally data analytics is performed by the analysts who convey their findings and insights to their business leaders along with product managers, marketers and sales executives through dashboards, reports and different other means.

But this process is quite slow when it comes to present-day business analytics cases, generally where real-time data streaming is involved. As data analytics is being built directly into different business processes increasingly, like in online commerce as well as customer support systems, the operationalizing and automating of the use of data as well as analytical content, along with speeding up of decision making is happening. Hence, automation of data analysis will be the key trend in the year 2020.

11. Augmented Analytics

Custom software development services of data analysis have always tried to inculcate the capabilities of their own technologies to a much wider audience of the daily business users as well as information workers. One of the main ways that it is happening is via the utilization of augmented analytics. It is defined as the usage of enabling technologies like natural processing language, machine learning, and artificial intelligence to assist with the data preparation deeply, generation of insights and explanation of results to augment how actually people explore and even analyze data and in how the entire analytical content is actually developed, shared and consumed.

13. Analytics enabled with Natural Language Processing

It is a well-known fact that natural language processing allows computers to understand human language easily. It makes it quite possible for the non-tech-savvy business users to query easily and ask complex data utilizing simple words and phrases, either via text or voice, and also receive easily understandable analytical results concerning their business. It is predicted that in the future, most of the analytical queries will essentially be generated by natural language processing or generated automatically or through search technology.

Conclusion 

Over the years, businesses have demanded actionable insights from the data they collect, and data analytics have been able to provide them with the same. Also, Big Data has certainly proven to be a great tool for businesses to make informed, calculated decisions based on the large volume of data stored, sometimes in data lakes.

However, with the emergence of the latest technologies like artificial intelligence, machine learning, natural language processing, blockchain, quantum computing, the entire Big Data cloud solutions is going to go through a massive transformation. Businesses will be able to get much deeper and accurate insights with these technologies. It can now get insights from dark data which hasn't been used for analytics and meaningful purposes for decision making. Meanwhile, data lakes have to prove their worth and businesses have to get compliant with regulations like GDPR in order to avoid penalties.

Here, we have actually outlined some of the key trends that will drive the big data technology market in the year 2020. Few of these trends may later prove to be way off the mark as we usher into the new reality of technological advancement and the dynamicity of big data. We will certainly witness some of these trends to massively transform the entire big data industry and bring in revolutionary changes and solutions.

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