The below saying has become a popular share around in social media:
“Big data is like teenage sex. Everybody talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
Indeed, there is quite a lot of hype around big data as for example told in The Big MDM Trend.
The teenage sex joke isn’t new at all. It has been used about a lot of new trends. I remember when the e-Business hype started, the joke was used here as well as you still can find some evidence about if googling the saying and getting this and that.
Today e-Business has matured and maybe a few brick and mortar bookstores have stopped laughing about the e-Business and teenage-sex joke now.
Also, maybe the joke says more about parents’ knowledge about teenage-sex.
Analyst firms have a lot of fun in making different surveys and rankings of vendors in different markets using their own special visualizing method. For the Master Data Management (MDM) market we have this year had the:
Lazy as I am I haven’t made my own survey but simply taken the brand names from the rankings mentioned above and filled in the name either 1, 2 or 3 times from each report depending on how well the brand was positioned.
So the size of the letters tells something about market positioning according to analyst reports. The size of the words also tells something about the length of the brand name. The placement is according to the wordle principle of course totally random.
And of course I now expect a load of tweets from vendor marketing departments saying that their company is positioned very randomly in the MDM Market Wordle 🙂
I’m sorry if this blog is turning into a travel blog. But here’s a third Paris story.
Boulevard Haussmann is one of the city’s great thoroughfares (to use the right meta-data term) and is known to be where we can find the headquarters of SPECTRE.
While visiting SPECTRE today I learned a lot about how SPECTRE is exploiting big data as an important way of keeping up with the tough competition in its industry sector today. But all that is of course a secret.
When asking about if they still has trouble with Bond the answer was:
“Bond? – Jimmy Bond? – The sexy data scientist who is working for NSA?”
“Oh no, I replied. James Bond.”
“Oh, yes” the SPECTRE chief data manipulator replied. “He was with British Intelligence. But he has been moved to the EU Data Protection Service. He just got his license to fine. Now 2% and soon 5% of our global turnover each time. Very dangerous man. Very dangerous”.
The mentioned issue is about the use of quotes in social data: A famous person apparently said something apparently clever and the one who makes an update with the quote gets an unusual large amount of likes, retweets, +1s and other forms of recognition.
But many quotes weren’t actually said by that famous person. Maybe it was said by someone else and in many cases there is no evidence that the famous person said it. Some quotes, like the Einstein quote in the Crap post, actually contradicts what they apparently also has said.
As I have worked a lot with data entry functionality checking for data quality around if a certain address actually exist, if a typed in phone number is valid or an eMail address will bounce I think it’s time to make a quote checker to be plugged in on LinkedIn, Twitter, Facebook, Google Plus and other social networks.
So anyone else out there who wants to join the project – or has it already been said by someone else?
LinkedIn is a great social service for professionals. I often read descriptions of LinkedIn with the sentiment that LinkedIn is a recruitment platform. However, in my opinion LinkedIn is much more than that. To me LinkedIn is more about networking, knowledge sharing, social marketing and social selling.
But that said, recruiters are certainly very active on LinkedIn. I guess it happens to me every week that I’m contacted on LinkedIn by a recruiter with a MDM (Master Data Management) job.
The opening is practically always like this:
“We are looking for a candidate with experience with <brand>….”, where <brand> is Informatica, Oracle, IBM, SAP and other well known brands in the MDM sphere.
As I don’t guess the recruiters make up the top requirement themselves, this number one requirement probably comes from the hiring organization. So to users of MDM, MDM is all about the software brand. Never mind people and processes. That’s easy. Technology is the hard part, not at least mastering the master data technology that was bought after a thorough selection process.
In here Jim ponders how working with Big Data must be build on a lot of other disciplines including Data Quality and the title of the blog post is nicely composed from the title of the fantastic Pink Floyd song called Another Brick in the Wall.
In this song there is an unpleasant voice of an angry stupid old teacher yelling:
“If you don’t eat yer meat, you can’t have any pudding. How can you have any pudding if you don’t eat yer meat?”
I’m afraid I also have to raise an equally unpleasant voice of saying:
“If you don’t eat yer data quality, you can’t have any big data. How can you have any big data if you don’t eat yer data quality?”
Many days I work in a so called day office, which is an office booked for a single day at a location convenient for where I am and is going to do on that day.
My day office today comes with a Rolodex.
But I have trouble connecting it with Bluetooth 🙂
Fortunately means of keeping a contact list has improved over the years, not at least when it comes to connectivity:
The Personal Digital Assistant (PDA) usually could do Bluetooth or had other ways to connect to other devices and share data that way.
With the rise of Customer Relationship Management (CRM) systems your contact list was blended with the contact list of everyone else in your company.
Now with Social CRM (SCRM) your company’s contact list is (or will be) integrated with social networks.
Data Quality challenges and opportunities also have changed with the development in how to keep a contact list:
The Rolodex was totally dependent on you keeping the data up-to-date and it was your choice how it was indexed – by given name, surname or whatever.
The PDA data should be kept timely by you as well. When exchanging with other devices different ways of organizing data could be a pain somewhere.
With CRM systems updates from third party sources became relevant and you aren’t alone on making the updates – differently. Duplicates and data not fit for your purpose is a pain.
Now with SCRM your contacts themselves may make most of the updates. Now you have to figure out which ones to rely upon and how to link with your old recording. In other words: Social Master Data Management.
Well, perhaps I better have to forget about using the Rolodex and get on with today’s tweeting. Now, where is my pencil?
I am a bit of a map addict. So when figuring out a visit to London City today I tuned in on Google Maps. When zooming in I got this map:
The pink establishment in the lower middle is the Royal Exchange, which today is filled up by luxury shops. First guess is that Google Maps has overlaid the map with positions from a business directory where Paul Smith was placed inside the building but Louis Vuitton due to a precision issue was placed outside in front of the building.
But there may be other explanations.
As the list of shops in the Royal Exchange shows here, there apparently isn’t a Louis Vuitton shop there.
So maybe Google Maps is timely real world aligned and Louis Vuitton was kicked out of the building (for being too cheap?) and now only has a booth on the steps in front of the building?
Of course, being a data quality geek, yours truly made a real world alignment check.
There’s no booth with bags (fake or real) in front of the building.
Paul Smith is exactly on the position within the building as shown on the map.
There’s no Louis Vuitton shop in the building.
There’s a Louis Vuitton shop, with only one bag with no price tag per window (so it must be real), in the next building behind the Royal Exchange.
It’s a precision issue with business directory positions on a map, where one is randomly spot on and the other isn’t. You can’t expect data quality luxury.
This morning people in the United States will not wake up to the date being 04/01/2013. Instead the date will be 01/04/2013 as it is in the rest of the world. The days of the mm/dd/yyyy date format are counted.
In a related statement a US government representative writes: What can be standardized must be standardised.
This is only the first step in a plan for the US to adapt to other more commonly used standards world-wide. The Fahrenheit temperature scale will be changed to Celsius by the 04/01/2014 for degrees below 0 Celsius (formerly 01/04/2014 and 32 degrees Fahrenheit). When spring comes along at the 01/04/2014 (formerly 04/01/2014) the change will be due also for all warm degrees.
In another move the United Kingdom has released plans for changing from driving in the wrong side of the road to driving in the right side of the road. There will be a phased implementation starting with lorries, then black London Taxis and red double-decker busses and finally all other vehicles.
The phased implementation is explained by a UK government spokesman by saying: We don’t believe in a big bang implementation.