It’s been a while since we brought you a recap of how BI and data analytics pros used Twitter. So, it’s high time that we get back to the recap.
This month we’re bringing you five things we learned on Twitter in the world of big data analytics in September.
Let’s get started.
1. Saul Sherry (@bigdatarepublic) interviewed our top data scientist Michael O’Connell and gave you a glimpse of his workspace.
We found this thanks to @KDNuggets. Here are three takeaways from the interview: Miles Davis makes for good analytics music; no data scientist is an island; and understanding customers’ business problems is crucial.
Read more here.
2. You need both goals and exploration in analyzing big data.
Dr. Anton Chuvakin (@anton_chuvakin), a research director at Gartner’s IT1 Security and Risk Management arm, wrote a great post on why it’s important to have both goals for your data and an interest in exploring your data.
Three takeaways from the post:
- You need both analytics and business hypotheses for your analytics projects.
- Clarifying your goals helps you understand your data better.
- While hiring a big data scientist won’t solve all your data problems, not having someone dedicated to data analytics gets you nowhere fast.
3. Data analytics will be the heart of insurance fraud detection within three years.
A new survey from Accenture shows how important data analytics is becoming to insurers, especially in fraud detection. In fact, 79% of respondents believe data analytics will be one of the most important business drivers for insurers in the next 36 months.
Takeaway: Not only does data analytics provide cost-savings, but as Accenture’s Eva Dewor (@accentureins) notes, it offers insurers “greater statistical certainty in cases of suspected fraud, a reduction in manual data analysis, optimization of the claims process as well as increased business productivity.”
4. Data analytics is getting really personal and it may spell opportunity for marketers.
Sure, we cover a lot of the business side of data analytics, but we data geeks love it all the time. In fact, Steve Smith (@MediaPost), editor of Mobile Marketing Daily at MediaPost, offers a refreshing look that has a good kind of hype – the data analytics we can collect on ourselves with wearable devices.
This movement of sorts is called Quantified Self. Smith outlines some of the personal data analytics projects popular in this geeky community in a recent blog post. Our favorite? Tracking differences in activities between twins.
A business note to take away from Smith’s blog – the opportunity marketers may have in seeing what data rebels are doing for themselves. He writes, “If marketers want to glean how they might leverage the data revolution to actually serve their customers and not just tag, track and target them, this is a space to watch.”
5. Hybrid databases may be the next big thing in enterprise big data analytics.
Eric Lundquist (@eslundquist) wrote a very popular blog on this topic for eWeek last month. In synopsis, he writes that today’s data is not the data of columns and rows. The unstructured data is transactional, social and opinionated. And the “scale of storage is huge, the query techniques are different (you often don’t know what you are looking for until the data is captured) . . .”
Takeaway: Traditional databases aren’t cutting it. Companies are calling for a hybrid approach to storing and pulling in data.
Read more about this innovation here.
The Five to Follow This Month + One More
Next Steps:
- Subscribe to our blog and follow us on Twitter to stay up-to-date on big data insights.
Amanda Brandon
Spotfire Blogging Team
