7 things to look out for in 2019: Changes for open source, data privacy, and the cloud
2018 has certainly been a year. As the days grow shorter, we can’t help but look forward to a brand new 2019 and all the amazing tech trends in store for us. We talked to Laurent Bride about the what’s in store for the world of technology in 2019: more questions about data privacy, improved open source, and increased growth for ML.
No one know what the future might hold, but we’re taking our best stab at it with some pretty educated guesses. The new year is just around the corner and we’ve asked a number of experts what they think is in store for developers in 2019.
Today, we’re talking with another expert: Laurent Bride, CTO at Talend. What does he see in store for the world of technology in the coming year? More questions about data privacy and security, increased support for open source, and possibly more clarity for algorithms in 2019.
Without further ado, let’s see what our expert had to say!
Open Source and Serverless
The market will double down on open source technologies
2018 has seen $53 billion in deals involving open source following the Cloudera/Hortonworks merger and acquisitions of Red Hat, GitHub and others. 2019 will see businesses double down on open source technologies — more investments and deals will get done, and open source communities will also pour more effort and energy into projects after having seen the opportunity for open source in the marketplace. To-date, open source has still functioned with a freemium model, but the coming years may see that shift as the enterprise finds value in conventional open source technologies.
Serverless will move beyond the hype as developers take hold
2018 was all about understanding what serverless is, but as more developers learn the benefits and begin testing in serverless environments, more tools will be created to allow them to take full advantage of the architecture and to leverage functions-as-a-service. Serverless will create new application ecosystems where startups can thrive off the low-cost architecture and creatively solve deployment challenges.
SEE MORE: Despite risks and side effects: “Open source will become even more important in the future”
AI/ML and Cloud
Questions around data morality will slow innovation in AI/ML
The past year has seen the hype around AI/ML explode, and data ethics, trust, bias and fairness have all surfaced to combat inequalities in the process to make everything intelligent. There are many layers to data morality, and while ML advancements won’t cease — they’ll slow down in 2019 as researchers try to hash out a fair, balanced approach to machine-made decisions.
The black box of algorithms becomes less opaque
Part of the issue with data morality with AI and machine learning is that numbers and scenarios are crunched without insight into subsequent answers came to be. Even researchers can have a hard time sorting it out after the fact. But in the coming years, while it won’t lead to complete transparency with proprietary algorithms, the black box will still become less opaque as end users become increasingly educated about data and how it’s used.
The business multi-verse expands through multi-cloud as data inefficiencies are solved
Multi-cloud promises tremendous reward if it can be used properly, but data inefficiencies and complicated compliance policies hinder progress for many. 2019 will see some of those data inefficiencies fade away as effective data strategies are implemented and new technologies unleash true multi-cloud functionality to the masses.
GDPR / Data Privacy
The “G” in GDPR will soon stand for “Global”
Data privacy regulations are going to become more widespread. For example, California, Japan and China are already working on their own regulations to adopt rules similar to the EU’s GDPR. Additionally, companies like Facebook, Google and Twitter have all severely mishandled consumer data, showing the need for increased and widespread data privacy regulations — even prompting Apple CEO Tim Cook to call for global privacy regulations. With consumers now viewing data privacy as a human right, increased data governance policies are sure to follow.
As privacy regulations spread, organizations will mistake data governance for data harassment
Based on what consumers do online, companies are able to determine, through their data, their demographics, interests and even what’s going on in their personal lives. This results in marketing so hyper targeted, it could feel like harassment. While organizations struggle to comply with privacy regulations and create more well rounded and informed views of each of their consumers, the lines between governance and harassment will blur, and there will be rocky roads as best practices are formed.