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Big Data Top Trends 2015 - Revisited

We look back at our prediction from 12 months ago and what actually happened

6Nov
Check Out Our 2016 Predictions: Big Data Top Trends 2016

In November last year, we looked at what trends we expected to see in big data in 2015.

Now that we are roughly 12 months on, we thought we would revisit this article to see if our predictions had come true:

In-Memory Databases

What we predicted: That in-memory databases were going to increase in popularity in 2015 and more companies would adopt them and benefit from real-time analytics.

What actually happened: In-memory has grown considerably in the last year, with companies like Uber now utilizing it extensively. Apache have even had a more widespread release of Spark, their in-memory platform that has allowed companies to scale their in-memory offerings.

Non-Data Scientists

What we predicted: That more non-data scientists would become more prevalent in data analysis and that companies would bring out software to allow less data driven people to work with complex data.

What actually happened: To some extent we were correct in that there are more people without formal data education becoming involved in data analysis and companies are seeing the benefits of this. However, there has not been as many fully automated data platforms as we thought we would see, although this may simply be something that is going to increase progressively over several years.

More Sensor Driven Data

What we predicted: That 2015 would be a tipping point for connected devices and the IoT and that the numbers would steadily increase.

What actually happened: We have seen significant strides forward in terms of the number of devices connected to the internet of things, but it's certainly not reached tipping point. Gartner have predicted that we will have over 13 billion devices connected by 2020 compared to the 2.9 billion currently. This means that although we have seen a significant increase this year (something like 1 billion devices) this is a fraction of what we will see in the future.

Deeper Customer Insight

What we predicted: That customer data would become increasingly detailed, making personalization more widespread and accessible to companies.

What actually happened: Customer data has indeed become increasingly detailed and more companies have created systems where customer data is multi-dimensional and they now know considerably more about each of their customers than they did. This has been done through relative simple elements, one of the most popular being the use of social media, which although used before, has become even more popular in the last 12 months.

HR Analytics

What we predicted: That HR analytics would increase in importance for companies across the world and that it would shake off the stigma of simply making employees a number.

What actually happened: The spread of HR analytics has taken place and we now have several more companies using it today than 12 months ago. With this spread has come the understanding amongst employees that they are more understood, not simply quantified.

No Ownership In Just One Department

What we predicted: That data will be democratized and spread across many departments, rather than being concentrated in just one.

What actually happened: To some extent this happened in many companies, but with the growing threat of cyber attacks that has come about in the past 12 months too, the importance of cyber security has had a certain limiting effect. Rather than data becoming more open, in many cases the security needs have trumped a more open approach. 

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