For most businesses 2020 has turned out to be a strange, uncertain year. Such turmoil puts more and more pressure on streamlining your business and finding out the best possible avenues for added revenues. And for this purpose, you already may have the keys for unlocking some of these potential improvements: your data. Whether it is exploiting data you already have via the use of new technologies, or focus on making decisions based on data, a novel view on how to approach this hidden treasure may open new possibilities to your enterprise. Let’s take a look at the four most prominent new data trends for 2020.
Leveraging Dark Data
The concept of Dark Data refers to unstructured, untagged, and currently untapped data. It is acquired through various computer network operations but not used in any manner to get business insights or make business decisions. Dark Data is not just another piece of Big Data: it is the fastest-growing new trend, holding considerable potential for those who can harness it fruitfully.
As per the study performed by IBM recently, it is expected that in 2020, 93% of data will be dark and unstructured. Companies can attain high-value results by merging both structured and unstructured data sets.
By its very nature, Dark Data is something that you already have - you just aren’t either using it or sometimes even are not aware of it. Leveraging of Dark Data is not entirely straightforward, but by tapping into it you can develop creative business solutions.
One of the biggest trends of the past years has been Artificial Intelligence (AI), and this year the trend is continuing to be one of the leading data processing areas. AI is on everyone’s lips as the next stage of digital transformation, and organizations are diving headfirst into AI projects to stay competitive.
Last year, IDC predicted that “global spending on AI is projected to top $35 billion in 2019 and more than double to $79.2 billion by 2022.” Despite the increase in spending, most organizations are still failing to realize value from their AI investments because of an early focus on getting acquainted with this new technology instead of effectively applying it on practical use cases.
We need to remember that the machine-learning recommendations still need real people making the final decisions. AI is just another, albeit effective recommendation tool helping in decision making, but the final go/no-go remains in the hands of specialists.
Using data as a resource
The value of on-time data as a real asset for businesses is indisputable these days. It can be used both in improving employee satisfaction aswell as business performance. The utilization is becoming business critical in the current competitive and demanding environment, yet not all organizations are not reaping the full benefits of it.
For corporations, transparency about their workforce data creates the opportunity to improve employee retention and satisfaction, which will then reflect positively on the communities and customers they serve. Organizations can analyze their diversity metrics on a granular level, pinpointing and correcting any systemicinequities.
Make data-driven decisions
How much do you know about your data? Do you know where it lives, who is using it, and how often? Do people in your organization know which data is appropriate for making decisions, and how to access it? Do you capture all the available data?
As explained by Tableau, data-driven leaders are differentiating their organizations with new solutions to integrate their distributed data pipelines—the roles and processes for how data is prepared, curated, and shared across the business are shifting alongside the evolution already happening within data technologies.
Solving data integration challenges is imperative for maintaining internal and external compliance and enabling the organization to get a complete picture of the business, understand customers and find new business opportunities. Many organizations are working to identify, prepare, govern and make widely available the data that most benefits the entire organization. The whole concept of data management is changing, beginning with the available and utilized technologies.
With a tailored approach that includes business users and objectives, broader data management initiatives have potential to succeed. IT and the business can share in the efforts to increase visibility, discoverability, and trust of their data environment. This also means the organization is empowered to identify and prioritize the data assets that are most broadly valuable, and better support governed data and analytics at scale.