Happy New Year to all our readers, let’s kick off the year by reviewing likely 2019 trends.
Beyond the inflated optimism that surrounds the start of a year, which trends are worth watching? Which are more than the analytics or tech equivalent of new year’s resolutions.
Well, this is only a subjective collection, based on my experience. However, each of these changes has been gathering momentum. Development has been happening for years and it now looks like real progress & relevance is likely in 2019.
2019 trends: Data Visualisation 3.0
So, building on the positive examples from IIB Awards 2018, that I highlighted last month, what is the trajectory for 2019? Well, I think this video from Elijah Meeks (senior data viz engineer at Netflix) highlights some important 2019 trends.
In this he not only summarises the history of data viz tool development, but also the changing expectations of users. He may well be right about the 2019 theme of convergence. A third wave, not just of tool convergence but of developers & readers expecting one more flexible tool & communication medium.
2019 trends: Self Serve Analytics tries again
There have been plenty of times when Gartner’s predictions of technology adoption have proven too ambitious, however they are always worth hearing. In a recent paper they predicted that by 2019 fully-automated or semi-automated systems would be delivering more analytics than data scientists (or analysts).
Now, I am old enough to have seen at least 2 other waves of BI/Analytics “self-service”. With many predicting the ‘democratisation’ of analytics, only to later find that business leaders would prefer an analyst to do the work for them.
However, with the rise of Machine Learning improving the intelligence & personalization of report/visualisation delivery, this time may be different. This article from Dataversity does a good job of considering how this might happen for BI. However, I think it stretches the term BI too far & misses the difference between the advanced analytics & data science work, where Data Scientists should focus.
Businesses will have to find solutions to the manpower gap, one of which is procuring, building, and deploying Self-Service Analytics and BI platforms to fill their in-house needs. Of course, merging technologies like Cloud, IoT, and Big Data also strengthen the “viability” of self-service platforms in the long run.
2019 trends: AI applications revitalise an antiquated trend (CRM)
We shared several posts on the state of AI during 2018, focussing on FS applications and even the issues of AI ethics. However, when worrying about potential threats to your career, it has become clear that many applications are over-hyped.
What we began to see in 2018 was a more mature production line to manage the delivery of AI products (including role of product manager). Several speakers at the Data Leaders Summit 2018 shared their practical experience in deploying AI models from lab to business lines.
So, I was interested to read this post on the reliable CX hub “Customer Think“, from Vince Jeffs of Pegasystems. In this post he provides a useful summary of how AI applications will evolve to better meet the CX demands for 2019. Including familiar topics like empathy, human-machine collaboration, data protection & ethics.
Jeff makes a good case for how AI applications will begin to demonstrate progress on all these fronts in 2019. An important milestone, if not yet the Sci-Fi destination of AI.
Tweet Yes, 2019 is only a few days old. But it won’t take long for five trends in AI applications to make headlines in CRM circles.
2019 trends: NOT the year that Blockchain transforms businesses
A strange one for me to finish on, but I thought it worth including this (non) trend too. Given we have focussed before on Blockchain, and the outstanding questions if it is to help Data Science leaders, this caught my eye.
The title is almost ‘clickbait‘, which is rare for a great site like Datafloq. However, the thoughts are worth reading. In this short post, Steve Jones helpfully summarises both the progress in business adoption & problem of still ‘over promising’.
Hopefully, wise businesses will continue to adopt blockchain technology only where it is a more appropriate data solution. That could achieve it’s status as a data source that begins to matter to data leaders for analytics too. But more likely is 2020 for serious use.
2019 trends: which waves are you preparing to ride?
But, rather than have too long a post to start our year, I’d prefer to hear back from you. Please use either the comment box below, or social media, to reply with your themes for 2019.
Which technology waves will you be riding in 2019? Are any essential to you achieving your 2019 goals? I’d love to hear your priorities or forecasts.
Have a great start to 2019!