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If we have learned anything from the pandemic, it is the fact that anything can change at any time. We also found we will adjust to the change, learn to live with it, and even take advantage of it if possible. Unpredictability is the rule of the game, and what follows could be very interesting or boring. However, it would be helpful if we knew what to expect.
In the furor of “digital everything” in the last three years, we’ve seen practically every firm transition to digital businesses through digital marketing. Everyone needs to be online, everywhere, at all hours, and that is where businesses can get engaged. Not being online means the business can’t generate money.
Also, for businesses to get engaged, they need to know what their customers want. To know what their customers want, they need access to their data. But there needs to be a restriction on the number of data businesses can access, or else hackers will take advantage of this loophole and steal as much customer data as possible for nefarious purposes. This is where data privacy regulations come in.
The Big Picture
More businesses realize this big picture day by day. They are slowly coming to terms with the growing importance of IT teams to digital compliance, successful digital strategies, and in the long run, business growth and success. They are looking to find out what protects data privacy, actively looking for the tools needed to do so. We now see companies allowing IT teams now play a more direct role in long-term company strategy and success than ever before.
Now that IT teams are in the driving seat, or, at least, the lead car in unpredictable times as we are, what should IT teams consider when implementing strategies that affect business aspects, and data privacy in particular?
Whether you’re a corporate executive, a small business owner, or even a homeowner, here are some critical data privacy trends that should be on your radar in the coming months:
Increased application of automation in data science
As machine learning and analytics become more widely used, IT staff will need tools that will enable them (data engineers and data scientists) to scale with ease. Scaling would help solve more challenges and increase the range of systems they can maintain. This will, in turn, result in the increased development of automation tools for data science’s numerous stages (some of which are feature engineering, data preparation, hyperparameter tuning, and model selection)
It will also cause an increase in the use of automation tools in aspects where machine learning systems such as data engineering and data operations are applied. Currently, many tasks in security and data science, IT operations, and software development are already being handled partially by automation tools.
More data control for consumers
Although this is not recent, it is becoming more than a trend. Consumers have been consistently pushing for the need to have more control over their data than companies currently allow.
In the coming months (and years), the trend will become much more intensive – there will be more furor and zeal about getting fairer data privacy standards. This will also push more consumers to opt for firms with a trustworthy track record when gathering and using personal client data. Customer data control entails being able to delete, download, or examine personal data whenever possible.
Increased applications for cloud data
Cloud platforms will only continue attracting enterprises now that many see the profit and ease of investing in the cloud. Other than the fact that they are providing better core technologies and managed services, software vendors and open-source data projects are progressively making their solutions cloud-compatible.
According to a recent poll, 51% of respondents claimed they already had some data infrastructure on the cloud, while other IT leaders expect to boost their expenditures in SaaS products. Data engineers and data scientists are beginning to employ new cloud technologies, such as serverless, for many of their tasks and projects.
Use of machine learning in businesses
Firms appear to be appropriately concentrating their initial machine learning initiatives (and spending) on use cases that improve their mission-critical analysis efforts, according to research.
For instance, automotive firms focus their ML implementations on product manufacturing, and financial services firms invest in machine learning for risk analysis. A trend that points to this is the rise of machine learning-specific technologies, such as data lineage, data governance, metadata management and analysis, and data science platforms.
Increased outsourcing by companies to MSPs
As more businesses strive to increase their digital presence, there will be a major shortage of IT experts globally. IT departments are overburdened, and the continuous digital revolution will result in highly competitive hiring and a significant rise in managed service providers (MSPs).
As hiring becomes difficult, a growing percentage of mid-commercial to mid-enterprise businesses will turn to MSPs to supplement their current IT teams. MSPs must be strategic in hiring and training to meet the volume and complexity of projects and tasks ahead.
Need Help Keeping Up with Data Analytics & Privacy Needs?
Your job may be ensuring sensitive data is secure. Our job is to help you with that process. We understand the importance of data privacy and have the tools and team to help you with it.
Twin State Technical Services can help your business with security systems that are compliant, adaptable, and AI-driven. To schedule a chat, contact us online or reach out at 563-441-1504.
