Every few months I devote a day to discover what the current trends in analytics are. I do this both to refresh the slides in my presentation and to refresh my mind to see what I may have missed.
The amount of literature out there on analytics continues to blossom at an amazing rate, making it a true challenge to stay well versed on what’s hot and what’s not. I read a new analytics themed book at least once a month and I follow dozens of blogs, web sites and social media groups. Being well versed on what is current in analytics is a key to success.
Every time I go to list the top 5 analytics trends, I find that some things change and some stay the same. Ever since I have been writing about analytics, data visualization is near the top. Business dashboards continue to be a big need. Business Intelligence (BI) tools evolve and new ones’ pop up, but Tableau continues to be a market leader.
That said, we are still squarely in an MS Excel dominated world. Upwards of 80% of Filipino professionals I recently surveyed still use Excel as their primary tool for data analysis. And even the ones who have dedicated BI tools, still use Excel for 75% of their analytics work. The adoption of BI tools is trending upward, but the curve is still very step.
Another trend that has been on the upswing is how more and more data is now unstructured data. The discussion on what is unstructured data and how best to mine it and integrate it with structured data has really been at the forefront for a while now. Going from 80% structured to 90% unstructured in just a few short years as mankind generates unprecedented amounts of data not easily captured in a database every day.
As October 2018, if I had to pick 5 current trends in analytics to talk about it would be:
(1) How to Conduct Impactful Data Storytelling,
(2) The Analytics and Data Science Talent Shortage,
(3) Using Big Data Analytics for Digital Transformation,
(4) Optimizing Data Warehousing and Data Lakes,
(5) Which Tool Is Best; Tableau or Power BI, R vs Python, etc
And thats is not even touching topics that are on the cutting edge like machine learning, artificial intelligence and augmented analyst. Although those are super important to an overall understanding of how we can optimize data, these topics generally are several steps down the road from where my audience sits. They are still trying to master the fundamentals of business analytics and introductory data science.
So I spend a fair amount of time looking for YouTube videos or TED Talks on these topics to add to what i read.
The amount of information available to consume if immense. I guess as we have more and more data and more and more tools to analyze data, we will have more and more people writing about how to use data.
Its a fun time to be the Data Guy.
DMAIPH – Decision-making, Analytics & Intelligence Philppines
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