Top 6 Data Trends for 2023
In an era where the landscape is constantly and rapidly changing, data analytics, science and engineering often act as critical factors in determining the degree of success.
At the end of a year, one can look back on the past year, or look forward to the new year. I have looked back through a few articles: ‘My first six months as a Data Engineer’ and ‘We Did It’.
This time I looked ahead while reading the tea leaves.
The Top 6 Data Trends for 2023
- Artificial Intelligence (AI) may be the single technology trend that will have the biggest impact on how we work, live and do business soon. With AI, companies can analyze data and gain insights faster than would ever be possible manually. This will be done using algorithms that get better and better at their job as they get more data. This is the basic principle of machine learning (ML), the form of AI used in business today.
- Data as a Service, or DaaS for short, is cloud-based software used to analyze and manage data, such as data warehouses and business intelligence tools. Essentially, it allows users to access, use and share digital files online over the internet. As users increasingly have access to high-speed internet, DaaS is expected to have greater reach as well. Using DaaS in big data analytics simplifies business review tasks for analysts and makes data sharing across departments and industries easier. As more companies turn to the cloud to modernize their infrastructure and workloads, DaaS has become a more common method of integrating, managing, storing and analyzing data.
- Data democratization aims to empower all members of an organization, regardless of their technical expertise, to be comfortable with data, ultimately leading to better decisions and customer experiences. Today, companies are embracing data analytics as a core element of any new project and a key business driver. Data democratization allows non-technical users to collect and analyze data without the help of data stewards, system administrators or IT staff.
- Data Analytics Automation refers to automating analytical tasks with computer systems and processes to minimize human involvement. The automation of data analysis processes can have a significant impact on the productivity of many enterprises. In addition, it has paved the way for analytical process automation (APA), which is known to help unlock predictive and prescriptive insights for faster wins and higher ROI. The technology will accelerate productivity and improve data usage.
- Augmented analytics is an important data science trend as its use is increasing day by day. It uses machine learning protocols and artificial intelligence to transform the way data analytics is processed, produced and generated.
- Data governance is the process of ensuring high-quality data and providing a platform to enable the secure sharing of data within an organization while complying with all regulations related to data security and privacy. By implementing the necessary security measures, a data governance strategy ensures data protection and maximizes the value of data. The lack of an effective data management program can lead to fines, poor data quality, biased business decisions, difficulty finding the right data, delays in analytics, missed opportunities, and poorly trained AI models.
Finally
With the continuous evolution of the digital world, organizations are increasingly using data analytics to improve the customer experience, reduce costs, optimize existing processes and reach a wider audience. In the years 2023 and beyond, more trends in data analytics are likely to emerge as we continue to develop AI.
About me
I’m Henk van der Duim, Data Engineer at Stichting amsterdam&partners.
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