Top Ten Data Analytics Trends in 2020
Table of Content
1. Conversational Analytics/ Natural Language Processing (NLP)
3. Commercial AI and Machine Learning (ML)
5. Internet of Things (IoT) Analytics
6. In-Memory Database/ Persistent Memory Servers
9. The Rise of DaaS (Data as a Service)
In the past few years, data analytics have become major players in companies across the globe when it comes to enhancing business efficiency. Data analytics have turned out to be the key parts of how you serve customers, hire people, optimize finance, manage supply chains, and perform so many other key functions in the organization. Businesses are ramping things up with more sophisticated and complex data than ever before.
Thus, industries and organizations are being greatly transformed by data and analysis. It not only helps to make more informed business decisions, but it also gives you the ability to market faster — backed up by real facts.
Companies House account data through data analysis gives you better insight into the financial performance of your business and a deeper understanding of customer requirements which, in turn, builds better business relationships.
As new company data and its face a 2020 reality check, there are a number of data analytics trends that lay the foundation for successful business deployment in the years to come. Here are the top ten trends to watch in 2020 all of which are designed to make you more stable and efficient in your business efforts.
1. Conversational Data Analytics/ Natural Language Processing (NLP)
NLP is the technology that can process human speech. Alexa, Siri, Google Assistant, chatbots, etc. are powered by NLP.
Hence, NLP offers an easier way to ask questions about data and to receive explanations of the insights. Conversational AI (Artificial Intelligence) analytics goes a step further by enabling such questions to be posed and answered verbally rather than through text.
Voice-enabled devices are becoming more and more popular in companies due to the ease of interaction it offers. This AI-enabled integrated voice tool offers many benefits including enhanced social listening, sentiment analysis, better personalization opportunities, and obviously, meeting any user’s standards.
You can better deliver the insights through conversational analytics simply by conversing with data. As a result, it hugely helps in the usage of chat-bots and other conversational-based interfaces. Therefore, this technology will definitely continue to rise as a trend in the business data analytics industry.
2. Graph Processing Data Analytics
Graph databases simply store and retrieve data like any other database. It is useful because it reveals relationships between organizations, people, and transactions. The application of graph processing ranges from anti-money laundering and fraud detection, to supply chain analysis, geospatial analysis, and many more.
“Graph empowers the connection and knowledge of different technologies through data. One of the examples of merging data is fitness applications connected to health news feeds.”
Graph databases use a set of analytic techniques to show you the connection of people, organizations, things, products, places, and their relationship with each other. The use of graph databases and graph processing will exponentially increase over the coming years. It will improve the preparation of more complex data.
3. Commercial AI and Machine Learning (ML)
Open source has been a big driver of artificial intelligence and machine learning, particularly at tech giant companies such as Google and Amazon. But the medium and small companies will need to leverage commercial platforms to manage their AI programs.
By the year 2022, maximum end-user applications that are produced in recent years will deploy ML and AI technologies. Moreover, these solutions will not be open source anymore, instead, they will be developed by commercials. The AutoML will prevent errors and make machine learning capabilities accessible to more employees across the enterprise — accelerating success and productivity.
It has been observed that with the growing trend of commercial AI/ ML use, the commercial vendors have started offering enterprise features to scale AI and ML, such as reuse, transparency, integration, management of models and projects, and new capabilities that are absent in many current open-source platforms.
This increasing trend in the use of commercial AI and ML will help to accelerate the deployment of AI/ ML models in production, ultimately driving business value from these investments.
4. Augmented Data Analytics
It will be one of the dominant data analytics trends in 2020 because it will enable companies to pick up valuable insights from data. When the companies conduct their survey for vendor selections throughout the following years, that’s when augmented analytics will come in handy. Many companies have already started fusing augmented analytics into their products and services to improve the experience for users.
5. Internet of Things (IoT) Data Analytics
IoT-enabled systems offer real-time intelligence to organizations. Large companies that deploy IoT devices rely on continuous intelligence with the help of the cloud, streaming software, and data from sensors.
According to various studies undertaken over the past years, by 2022, more than half of the major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.
So it’s evident that we are going to see many more analytics solutions for IoT devices that will provide not only relevant data to businesses of various sizes — but transparency too. However, it is also true that the majority of global organizations will be hindered from achieving the full benefits of IoT due to a lack of professionals in the data analysis field.
If you have ever come across smart devices like Google Assistant or Microsoft Cortana, then you know how IoT is grabbing continuous attention from users. Thus, it will encourage businesses to invest in this technology, especially in smartphone development as it uses IoT the most.
6. In-Memory Database/ Persistent Memory Servers
Most database management systems use in-memory company information database structures. On one hand, the data volumes are growing rapidly and on the other hand, the memory size is restrictive. As a result, new server workloads not just need to speed up the performance of the memory processor, but they also need massive memory and quicker storage.
That’s where persistent memory technology comes into the picture. This technology will help businesses extract more actionable insights from available data. Many companies are experimenting with persistent memory. These in-memory database servers give you affordable performance, larger memory, and less complex availability.
Some database vendors are already rewriting their systems in order to support this type of server, which enables the analysis of more data, in-memory, and in real-time.
7. Blockchain Technology
Blockchain has already taken over most of the major industries across the globe which includes the retail industry, real estate, online marketing, banking industry, education and healthcare, the sports industry, government, voting, music and entertainment industry, cloud computing, and so on.
Blockchain can be of great help for startup companies data and the companies themselves. To be more precise, startup businesses can effectively become the early adopters of blockchain and leverage its benefits in terms of making improvements in their supply chain management, payment and money transfer, customer support, promotion and advertisements, security and protection of their digital identity, fund generation and the list can go on.
And these are just a few examples of why blockchain can be promising for startup businesses. With threats of security and inefficiencies prevailing in the business world, blockchain adoption enables you to deal with it effectively and efficiently.
8. Data Fabric
“A data fabric is an environment that standardizes and unifies data from different sources, different storage locations, and different access points to make it usable, scalable, and integrated.”
Data fabric creates a unified framework that supports agile data and makes it seamlessly accessible. Gartner has predicted that by the next year, most of the major businesses would be forced to invest in creating data fabrics to improve their business intelligence. The UK company data and database transformation are inevitable due to the plenty of benefits it gives to enterprises — that obviously include overcoming the most crucial challenges: reliability, scalability, and availability.
As said by David Menninger, Ventana Research SVP and Principal Analyst, “organizations that adopt a shared fabric among their data and analytics technologies will have an advantage over those that retain a siloed approach.”
9. The Rise of DaaS (Data as a Service)
Data as a service (DaaS) is a cloud-based technology allowing customers to access digital files via the internet. DaaS will make it easier and quicker to share data in real-time, thus improving productivity within the business. The globalization of DaaS will also assist in bridging gaps between organizational departments that need to share data but currently don’t have the capacity to do so.
10. Data Analysis Automation
We know that the massive increase in data production and data provider company, data storing and data processing has forced businesses to incorporate automation for handling the vast pool of data.
Business Intelligence or BI has always provided solutions for the consolidation of all the data. There are various different methods for discovering, analyzing, measuring, monitoring, and evaluating the data. BI is a growing trend in 2020 which will continue to bring automation possibilities for easier data collection, analysis, and reporting. With automation around, businesses responsible for the developing data analytics software will be able to focus on simplifying data science products and allowing easier use.
Conclusion
In conclusion, it can be said that In 2020, data and analytics are already a significant part of businesses all across the world. Big, medium, as well as small companies, have already understood data analytics as an important source for making more informed decisions in recruitment, marketing, branding, and many other areas.
It’s a smart move to stake at top data analytics trends 2020 to keep your business ahead of the game towards a more competitive future. So you can take help from these trends to analyze where you need to improve your business processes in order to achieve maximum growth and ROI.
If you are thinking of incorporating these trends in your business development, you will need expert opinions and consultations by specialists from a reliable data analytics company with a strong project background and portfolio. Company data provider such as DataGardener is capable of assisting you in this regard and they are readily available for consultations regarding the details of your project, pricing options, and time of the project implementation.
