Despite the warnings from Tony, I am going to risk sharing viewpoints on trends for 2017 (this time in the world of data & analytics).
However, as with our previous collection for research, this is not intended to be a definitive forecast (if that isn’t an oxymoron anyway). Rather, I’m sharing this content in order to prompt topics for data & analytics leaders to consider.
So, if you are currently pulling together your 2017 plans, here are potential opportunities or capabilities to consider.
Let us know your views on these trends & any that really influence your plans for this year.
Data trends for 2017
Let’s start with one of the most overt prediction posts (which is really just highlighting emerging trends). I agree with a number of the points raised by this post from O’Reilly Media Blog. There is a growing need for focus on data infrastructure issues (the need for Data Engineer roles) and more companies are looking to store data in private ‘clouds‘.
But, I take a different view on two of Ben Lorica’s predictions. I’m not sure more data scientists, or companies, will use deep learning. I suspect this will remain niche for some while, until it has proven commercial relevance to a wider range of businesses. On Ben’s final trend, I don’t so much disagree as have a different emphasis. Rather than the data community having time to ‘hammer out solutions‘, I believe 2017 will see more & more leaders get serious about GDPR compliance and planning the changes needed to achieve that.
See what you think…
Get the O’Reilly Data Newsletter and receive weekly data news and insights from industry insiders. The following piece was first published in the Data newsletter. The data community will have plenty of opportunities in 2017-and a few gnarly challenges. Here’s a look at what lies ahead.
Big Data trends for 2017
Over many years, KD Nuggets has established itself as an expert hub on the topics of Data Mining & Data Management, so it’s interesting to compare the themes identified by experts they interviewed.
Many of the commentators agree with the high-level themes identified in the above link, that is a growing emphasis on:
- Greater use of AI & Deep Learning (guess I’m in a skeptical minority)
- Further use of data from Internet of Things (home devices as well as wearables)
- Some specific technical developments in Apache Spark 2.0 (driving greater take-up)
- Greater focus on CDO role & data regulation (especially in light of GDPR)
Some useful highlights in progress seen during 2016 are also summarised. Not a long post & worth reading (as are the other 2 in series):
At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon.
BI and Analytics trends for 2017
Normally, when advising clients, I am helping them distinguish between Business Intelligence (BI) and Analytics. Too much focus on the former can seriously undermine the investment & skills needed for the latter. However, in this article from the DataPine Blog, Mona Lebied does manage to highlight some other themes that matter for analytics.
In addition to her emphasis on BI (which is still a development area for many businesses, despite commentators emphasising advanced Data Science), I think these themes matter for analytics in 2017:
- Data Storytelling & Data Journalism (which I predict will become a key writing & interpretive skill for 2017)
- Visual Data Discovery (building on interactive data visualisation to aid exploratory data analysis stage)
- Cloud Analytics (will enable many firms to fast-track analytics capability rather than wait for ‘in house’ build – if suitable)
- Data Governance (as already mentioned, to be a key theme for 2017 & I will write further on readiness for GDPR)
- Predictive & Prescriptive Analytics Tools (will prove tougher than expected to get write, but businesses need forward view)
Here is the article, which may also help your thinking if you also have responsibility for BI within your bailiwick:
Over the past decade business intelligence has been revolutionized. Data exploded, and became big. We all gained access to the cloud. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts.
What are you considering?
I hope those 3 lists have prompted some consideration of what tom include in your 2017 plans. Any others on your lists of trends for 2017?
Have you got a clear strategy for Customer Insight, against which to compare your progress & identify gaps to fill?
As well as the predominant emphasis on technology & process/regulation above, do remember to also consider softer skills. From my own experience in leading data & analytics teams, developing the right ‘softer skills’ in analysts made more difference than correctly guessing which technology or technique to use.
I wish you well with your 2017 data & analytics plans. Do let us know if there is any content you’d like us to cover in more depth this year.