From These Organizations:
- Center for the Study of Economics
- Campbell& Co.Ltd
- Professional Economic Counselors Inc
- Merrill Lynch
- Maryland Southern Christian Leadership Conference
- Community and Regional Resilience Institute
This was originally published on Rev’d, the blog belonging to Content Rev
Data is power.
A friend of mine likes to visit boot fairs and low value auctions. He’s got a great eye and will often come home with a delicate set of antique silver spoons, bits from an old grandfather clock or some old table.
“Very collectible,” he will be heard to say of his early morning bargains as he sets about restoring furniture or giving the brass on a magic lantern a bit of a rub. Stuff is repaired and piled up in various rooms in his house.
His plan is that he will sell most of it on eBay, and indeed he has made some killings with items bought for a few pennies being sold for hundreds of pounds. The problem is that while he may sell a few things every few months, each week he is accumulating far more.
And there is the rub. If he was able to get on top of his ever-increasing pile of clutter he would generate a not insignificant second income, but he has a fulltime job and sees his rummaging and collecting as a hobby.
And how many businesses may have the same challenge? When it comes to digital data, businesses are increasingly rich, data is piling up across different databases, but are they succeeding in building “Big Data” and extracting the maximum value? No, inevitably they are not, especially when the data is not seen as a primary revenue source.
In business-to-business (B2B) publishers and other organisations many companies are sitting on hugely valuable data assets. But legacy systems, or even the business models, act as a barrier and an apparently insurmountable hurdle to cashing in and exploiting digital data assets.
Data Never Sleeps
Let’s stop for a moment and consider what is going on around us. Here’s an infographic from business intelligence company DOMO via Neil Spencer at Visual News that touches on the accelerating scale of data:
Data never sleeps. Every minute massive amounts of it are being generated from every phone, website and application across the Internet. Just how much data is being created and where does it come from?
And so, you need to ask five questions about your data:
- What data are you are sitting on?
- What data are you creating?
- What data are you capturing?
- Do you know the value of that data?
- Do you know how to extract the value from that data?
What Is Big Data?
Data can be numbers, text, video or any form of content, but while data can be anything, Big Data is everything. The old school view of data was as lots of ones and zeros, or numbers on a spreadsheet. Yes, it is true, but the true value of data comes when they are added together and comes to mean something, to offer a conclusion. So, a list of customer names, contact details and preferences becomes a prospect list; a spreadsheet of numbers becomes a graph, an infographic can become a news story that tells the reader what is happening.
Big data takes it a stage further, but it brings the challenges of how to effectively capture, store, search, share, analyse and visualise the data. It is complicated, but if the value is to be extracted, it makes sense to invest in building a system that enables a single view.
Moving beyond customer data, some publishers are also gaining value from their data. It makes no sense to have dusty archives cluttered with loads of stuff that may come in useful. This old stuff has value and it is your job to find out what that value is. At a time when traditional publishing models are under threat as never before, some publishers are creating new digital data products, where they are distilling the statistics, reordering them, packaging them in such a way as to make them easily understandable or visually appealing, and then selling that data wrapped inside new data products. They are then delivering them across numerous digital channels.
There is a growing school of data journalism. The point here is that while in the past a journalist would need a “nose” for a news story and then spend time trying to develop it, today that journalist could spend time making sense from mountains of data. While the news may be breaking via Twitter and other social media platforms, the data journalist could be the first to make sense of the impact of that news event. Knowing something is happening is one thing, but understanding the consequences could be far more powerful. As a simple example consider the British parliament MPs scandal when mountains of data was sifted to report on one of the biggest scandals ever to rock the British establishment. For the Daily Telegraph, the newspaper to break the story, it resulted in massively increased sales and global attention.
An interesting point here is that data journalism should not be limited to traditional publishers. In an era when every organisation is a publisher, data journalism captures an activity which aims to make sense of something for the target audience.
So, if a B2B publisher wants to help its audience understand market trends, it can turn to data journalism. If a legal firm wants to help employers (its potential customers) understand trends in employment law it too could turn to data journalism to offer insights into its data on employment tribunals and the outcomes.
None of this is easy, but if we accept knowledge is power, then when thinking about digital data, that data is both the fuel and the engine that drives knowledge.