Over the years, big data has significantly impacted industries that highly rely on data, such as healthcare, retail, e-commerce, government, online banking, and online customer service network.
The data analytics industry will grow as more businesses adapt to data-driven models. A survey found that 27% of business executives believe their organization is making money from big data initiatives. Although big data appears to have the edge, business leaders are concerned about its challenges.
These challenges include technical incompetence, difficulties integrating data, and data silos. The data management industry continuously pushes technological boundaries with innovations like cloud computing and new IT architectures to address all these challenges.
Undoubtedly, data analytics has revolutionized processes in multiple sectors encompassing education, environment, economics, healthcare, and more. Also, each is using data to make better decisions.
There is a steady rise in entry, mid-level, and advanced-level data analyst jobs, which may increase in 2023. Moreover, the demand for data analysts is expected to increase as more industries rely on big data. Given the demand, you can develop new skills that could lead to better career options. You can do so by signing up for any data analytics bootcamps online and gaining a thorough grounding in the field.
Seven Data Analytics Trends
Today, we will go through some of the top data analytics trends expected to be followed in 2023 and beyond. Following these trends may help businesses better adapt to data-driven models in their processes. And potential data analysts will know in which areas they need to master skills to integrate the models.
Data Democratization
Data democratization empowers a company’s workforce to use the data to help make informed decisions and offers a better customer experience. In short, as data analytics become more prevalent, not just data engineers and data scientists – will be empowered to use them in their daily work.
It has led to new forms of augmented working, in which tools, applications, and devices allow users to access intelligent insights to perform their duties better.
Data will be vital to businesses in 2023 as they strive to understand their customers, develop better products and services, and streamline their internal operations to reduce costs. According to McKinsey research, companies that allow their entire workforce to access business data are 40 times more likely to report a positive impact of analytics on revenue. Nevertheless, it is becoming increasingly apparent that this is only achievable once technical and non-technical staff are empowered to act on data-driven insights.
Creating a democratized data environment in an organization will help significantly manage big data and better comprehend its potential.
Augmented Analytics
Analyzing data involves producing insights from it, usually by generating queries and reports based on user requirements. Currently, this trend in data analytics uses machine learning and natural language processing to automate the generation of analysis reports, which would otherwise require professional data analysts to devote days or weeks to preparing them. Augmented analytics will enable business users to gain instant insights from the data without developing data pipelines in advance.
Edge Computing
Edge computing involves bringing computing and data storage closer to the data source. The result is improved data accuracy and management, reduced costs, enhanced decision-making, and more efficient operations.
The introduction of 5G has given rise to a wide range of edge computing opportunities across many industries.
A significant benefit of edge computing is that it consumes less bandwidth, which makes it an efficient way of processing enormous amounts of data. As a result, the amount of data processed at the edge may increase significantly, up to 75% by 2025 from 10%.
Moreover, IoT devices are integrated with edge computing. With this integration, IoT devices have increased flexibility and agility and have sped up the processing time. It is also capable of performing real-time analytics. Operating software from remote locations is also easy and manageable, all thanks to edge computing. Hence, this trend will become more prevalent in 2023, given companies and businesses are increasingly employing remote workers.
Hybrid and Multi-Cloud Solutions
The advantages of moving data analytics solutions to the cloud include the following:
- Cost savings.
- Availability of a wide range of resources for data analysis.
- The ability to scale easily.
Cloud computing enables organizations to provide their employees with the tools to collect, sort, and share data on demand.
As the cloud becomes more affordable, reliable, and secure, data analytics can play a more significant role in the day-to-day operations of organizations.
By providing their employees with faster access to structured, unstructured, and real-time data, hybrid multi-cloud solutions can allow organizations to solve their data volume and latency-related issues.
Data Fabric
Data fabric is a collection of architectures and services that deliver end-to-end solutions, covering multiple clouds across an array of endpoints. This architecture provides a standard data management solution for various on-premises edge and cloud devices.
This trend will become increasingly popular as businesses speed up their processes and data becomes more complex. It is easy to use, repurposable and can be combined with different integration styles, data hub skills, and other technological advancements to create an integrated system. In addition, data fabrics facilitate data usage within an organization by reducing the time required to design, deploy, and manage data operations.
Data Governance
Data governance refers to ensuring that high-quality data is shared securely throughout an organization while adhering to privacy and security regulations. Data governance strategies provide data protection and maximize data value by implementing the necessary security measures.
A lack of an effective data governance program can result in many problems, including compliance violations and fines, poor data quality that will affect business decisions, difficulty finding appropriate data, delays in analysis, and missed opportunities. Data democratization coupled with data governance allows data to be incorporated into all aspects of decision-making, thereby increasing user trust, enhancing brand value, and reducing compliance risks.
Data as a Service (DaaS)
According to estimates, the data as a service (DaaS) market will generate 11 billion dollars by 2023. It has reached the point where even the most minor players can enter the market and generate revenue.
DaaS is one of the efficient ways to generate revenue if the data generated by your organization is valuable or of significant use to others. Therefore, now is an excellent time for you to consider rethinking your data offerings and finding new ways to contribute.
Wrapping Up
In recent years, startups, small and medium-sized businesses, and large organizations have used data analytics to improve productivity, reduce costs, and reach more customers. In addition to these benefits, big data’s ability to enhance critical information security attracts many companies’ attention. As technology advances, more data analytics trends will emerge and flourish during the next few years.
These above-mentioned data analytics trends indicate that businesses worldwide are becoming more data-centric. The emergence of artificial intelligence (AI), the Internet of Things (IoT), and automation in our everyday lives has underscored the importance of recognizing these trends since they can provide organizations with the tools to deal with the increasing number of uncertainties and changes. Consider significant trends that align with your strategic business objectives, experiment with these trends, and then aggressively invest in them.