Big Data Trends in 2020: All You Need to Know

Introduction

Big data in simple terms mean the large volume of data – both unstructured and structured. Big data trends in today’s times is a well-established technology and is all set to provide eye-opening insights.

Big Data Trends for 2020

• As the volume of data continues developing, the requirement for data professionals is at an all-time rise. A CDO is a C-level authority at risk for data integrity, security, and availability in a company. Today, enlisting a CDO is the norm.
• Customer journey analytics and real-time speech analytics are gaining popularity, with the aim to improve the client experience and enterprise productivity.
• Multi-cloud deployment will gain huge importance, bringing the hybrid and multi-cloud philosophy to the front line of data ecosystem strategies.
• Actionable data that indicates the missing connection between big data and business prepositions will be in huge demand. Big data in itself is useless without assessment, thus with data stream handling, data can be divided immediately. This holds more value to companies and organizations.
• Continuous intelligence – a framework that has integrated real-time analytics with business operations, uses several technologies such as optimization, business rule management, and machine learning. Gartner has predicted that more than 50% of new business systems will utilize continuous intelligence by the year 2022.
• Machine learning (ML) is another feature that is expected to impact our future fundamentally. ML is a rapidly developing advancement used to expand business processes and regular activities.
• Spark and managed Spark solutions such as Databricks will be the preferred solutions as they are considered to be much better than Hadoop.
• The number of IoT connected devices is predicted to be around 75 billion by the year 2025. Thus, we can see where big data is originating from. Digital transformation as IaaS, IoT, AI and ML are behind big data, and will push it to new heights.

Some of the big data technologies trending in 2020 are:

• Artificial Intelligence (AI)
• NoSQL Database: Incorporates a broad range of separate database technologies to design modern applications.
• R Programming: A free software used for statistical computing, visualization, unified developing environments such as Eclipse and Visual Studio assistance communication.
• Data Lakes: A consolidated repository to stockpile all formats of data in terms of structured and unstructured data at any scale.
• Predictive Analytics: A subpart of big data analytics, tries to predict future behaviour using prior data.
• In-memory Database (IMDB): IMDB is stored in the main memory of the computer (RAM) and controlled by the in-memory database management system.
• Blockchain: Assigned database technology that carries bitcoin digital currency with a unique feature of secured data, which once written can never be modified.
• Hadoop Ecosystem: The Hadoop ecosystem comprises a platform that assists in resolving challenges surrounding big data.

Challenges with Big Data

Following are some of the challenges that lie ahead for big data:

• The main challenge in terms of big data is that of volume. Data is increasing at an astounding pace and companies are facing challenges in terms of space to store data for correct analysis. The increase of unstructured data complicates the situation further.
• Another challenge is the availability of skilled big data professionals.
• Providing insights timely fashion is a huge challenge. Big data cannot be kept idle by organizations in repositories– it needs to be analysed immediately.
• Big data is a broad array of data sources. Integrating all these sources is not very easy.
• With an increase in cybercrimes, privacy and data integrity are at constant risk in organizations.

Conclusion

Despite the challenges it faces, big data is here to boom and the opportunities associated with big data are limitless.