Big data: a useful term?
Last year’s Measurement and Analytics report found much ambivalence towards and misunderstanding of big data.
Indeed, 8% of respondents thought that big data was a ‘pointless marketing term’.
We asked respondents ‘what effect has big data had on the web analysts in your organisation?’ and, as you can see from the word cloud, ‘none’ was the overwhelming answer:
So has 12 months made a difference to attitudes and understanding?
What does big data mean?
We asked 446 company respondents whether they agreed or disagreed (or were neutral) about a number of statements relating to big data.
The results suggest a more positive sentiment towards big data, with 76% agreeing that it has uncovered optimisation opportunities which would not otherwise have been possible, while 47% see it as the best way of bringing online and offline data together.
Big data is nothing without the skills required to make use of it, which has led to the role of the ‘data scientist’, combining skills such as statistical analysis, programming, modelling and analytics.
This new job title comes with higher salary expectations, and represents a natural evolution from the analyst role, but one that has an exploratory nature and a certain degree of business acumen.
Anjul Bhambhri, vice president of big data products at IBM, described the data scientist as:
…somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organisation.
Q: What makes data scientists different from analysts?
The chart shows that around three in five (64%) organisations surveyed perceive data scientists as analysts with statistical skills. However, less than a third (30%) think that data scientists possess programming skills.