The big data is one of the fastest-changing and fast-paced aspects of the tech industry. Big data affects how the entire world is operating in the tech space and more industries are employing big data tools to streamline their data and analytical operations.
In 2020, we are sure to see more development in the big data space that will influence business intelligence and information processing. Various factors influence the growth of big data and it’s one of those aspects of technology that grows with its users and responds with innovative solutions to manage data and analytics.
With information becoming a valuable commodity, it is important to look for new and emerging trends in 2020.
- More accessibility
In today’s world, various industries are becoming accustomed to the concept of democratization and decentralization. The concept of decentralization also applies to big data. In 2020, we will see the development of more accessible big data applications and warehousing tools.
The wider accessibility will allow ordinary employees outside of the IT department to access and understand data. This will allow companies to make better use of data by identifying challenges and potential growth areas for a business or department.
The automation and accessibility of data have fed into many aspects of a business, including marketing and assessing ROI. As a result, 40% of data science-related tasks will be automated making it simpler to data-driven decisions.
- Natural Language Processing
Another big thing that will take place in relation to data and Natural Language Processing is that Business Intelligence (BI) and Big Data will become more readily available. BI will be turned into a conversation with a chatbot and normal everyday language will be utilized to initiate queries.
The greatest part is that these queries will be made on-the-go on smartphones as the need for GUIs is eliminated. The processing of those queries is then handled on the cloud. That makes data mobile friendly and cost less to access because no specialized setups are required.
For example, Spark NLP is used to process text for the Python, Scala and Java languages and is based on Apache Spark. It has been used in various industries to provide businesses with key insights about customers behavior.
- The merger of the Internet of Things and Data Analytics
With over 20 billion IoT devices anticipated to collect data for analysis in 2020, it can be expected for companies to begin using IoT devices to manage operations.
There is a growing need for data analytics to run more intelligently and this means that businesses will use the devices to generate accurate data. The merger of the two aspects will require the expertise of more data science professionals who can guide processes and operations.
- The use of DataOps
In 2020, data pipelines will take center stage in various organizational structures and this is in response to the increased number of systems and data volumes. This means that businesses will need to employ advanced data analytical tools in their organization. DataOps will allow a business to keep up with the fast-moving developments in data development.
Although DataOps is not a new concept or approach, it will optimize businesses to be able to deliver accurate data. Businesses are also going to use the tool to further invest in data management, analytics, and machine learning.
- Experiments with blockchain technology
A few businesses have already started investigating how blockchain can create new business networks and business models. This will continue in 2020, and more developers will look for strategies to incorporate blockchain into their data management models, both I private and public sector.
Over the past few years, certain hurdles have affected the full adoption of blockchain frameworks and these include issues such as scalability and the complexity of the technology itself. Despite this, many businesses are optimistic that it is possible to create new business networks using blockchain technology.
- Increased in-memory computing
In 2020, we will see more organizations and businesses adopt in-memory computing because the cost of memory tech will dramatically decrease. The lesser cost allows for more accessibility and businesses will be able to make use of technology that drives accurate data-driven decisions.
The use of in-memory computing allows businesses to create highly intuitive data environments leading to improved real-time machine learning, data analysis, and easily accessible analytics.
- Data-as-a-Service
In 2020, there will be an increase in companies offer data-as-a-service (DaaS) and this increase with result in users being able to use and access digital files online. The recent development is an extension of using data for decision making and companies realize the potential of investing in data management resources.
DaaS is a sure way to assist companies in increasing their productivity and in gaining valuable insights into how they can improve operations and initiatives. This trend will pave the way for more cloud-based resources and it will become more affordable for businesses to use less intensive storage methods for data.
- Increased data governance
Governments across the world are realizing the need for increased regulations when it comes to data governance. This has become important big data is polarizing across industries. The way data is managed has changed, and is dictating the direction of information management.
This means that governments are now under pressure to respond with relevant policies. In some countries, regulations have already been passed, such as the California Consumer Privacy Act of 2020, and hailed as a law that is highly relevant to the use of the internet. These policies will ensure optimal security, careful data management, and unbiased consumer profiling.
- Increased use of Apache Arrow
Apache Arrow is expected to reach up to 1 million downloads per month and has become an industry standard for in-memory data representation and sharing. The technology has certainly played a role in speeding up data operations and has powered numerous open-source and commercial technologies.
Apache Arrow has grown at a rapid pace and continues to do so because it has simplified data science and increased speeds. Its recent release of the latest version in October 2019, features new technology such as Remote Procedure Call (RPC) and increased inter-use of data. Apache Arrow will take over many systems by 2025 and become a default in data communication systems.
Conclusion
The ever-changing nature of big data is evident in these predicted trends, and the truth is that big data is mostly unpredictable in what will happen next. However, the increased need for accurate data in business is the driving force behind the rapid growth of the industry. 2020 is an exciting year for new developments and it will be exciting to see the direction big data grows over the coming years.
