What is 2thinknow Interchangeability and Standardization?
2thinknow data is designed to deliver a consistent story. This means that data across data points should be consistent, or have a note to explain inconsistencies.
Is this not already the case?
No, no, no. Ever wondered why every news article or report has figures that seem to contradict each other?
Many figures have different assumptions, definitions, methods and thinking. Also numbers are often misquoted.
So the data you get from 'sources' is often broken and not comparable.
ie. data from U.N., OECD, World Bank, Local government, governemnt agencies, credit bureaus, is mismatched. Badly. Geography, populations, assumptions. It's a real mess.
How do 2thinknow fix this mismatched data?
We have specialised knowhow
Can I provide you our data and can you fix it?
Yes, we can handle your data-sets, and fix your data and make it standard. Such work is done by the hour. Please request a Proposal.
What is a simple example of data often misquoted in news?
For example the U.S. economy is still the largest, unless the E.U. is compared like for like, in which case the E.U. is the largest economy. China is then third. If this is adjusting for purchasing power, then China is number one.Despite inequality in U.S. and China especially, the U.S. remains technically the largest nation economically. Most of this is not properly explained or understood.
It is too simple to say China is larger than the U.S. at this time, as purchasing power is a series of assumptions about price, and such statements are based on GDP (Gross Domestic Product), which itself is problematic.
Another example is crime figures, which record crimes reported, and may be in a different geographic area to a city. ie. patrol statistics of crimes officially recorded may only apply.
Why does population definition matter to your work?
In the case of some cities such as Sydney or Melbourne these are easy,as all definitions are relatively similar. However, even in this case the City of Melbourne (formal city) does not include suburbs. So if you retrieve statistics even in a simple case from a government website this would not reflect the whole city, just the rather small CBD and inner suburbs. A walkable distance, not a city of a few million.
Meaning without knowhow, comparing data for the cities from 2 sources will likely be mismatched. That's where 2thinknow help with consistency in comparability.
Why did 2thinknow create Urban Definitions?
To make it easier for you. 2thinknow Urban definitions measure what most local people would consider the 'city'. Think of them as functional definitions of a city.
Do 2thinknow offer Metropolitan Area definitions as well?
Yes, we offer most data in Metropolitan Areas (also called MSA). This helps if you have existing data in this format.
What is the problem with many city definitions?
For many cities there are multiple definitions.
If you don't ask, you will likely compare the wrong data and make large mistakes in your data.
When under time pressure this is not good and many sources are not clear on the basis of their data.
What is an example of mixed city definitions?
for European cities this is complex, as there are so many definitions. Many of these don't match what you would consider the city, or vary by source (even governmental data). So definitions are often for specific government or political purposes, and may not match what you need - let alone between sources.
Berlin population can be 80% higher between sources. Making data comparison hard. Yet all 3 definitions are 'correct' technically.
Is this the same in the USA & Canada?
Even the USA and Canada among others can have 3 or even 5 city definitions. Many people are not aware for example that Silicon Valley spans 2 U.S. cities (MSA) in statistics. There are 7 common definitions of the Bay Area alone. The Chicago government definition includes 2 other cities, and New York metro includes parts of 4 states.
What about Asia? Same city definition problems?
City definitions can also include large parts of rural areas -- not part of the city. Chongqing can be defined as an 8 hour drive (province not a city).
Why is this a problem?
If you don't understand it you will make mistakes. You are comparing data that means different things in different locations. That's a lot of the reason data doesn't look 'rgiht' when you view it. Even prominent newspapers make this mistake, so it is hard to avoid without expertise.
So why do 2thinknow Urban Definitions solve this problem?
Because we use common sense definitions of the cities, that accord to what most people would consider the 'city'. These are also harmonized across multiple data sources.
Which definition should I choose?
Most people want to compare actual cities should choose Urban Definitions, the default and cheaper option.
If you need inter-operability with other data-sets you already own for research, then choose Metropolitan Area definitions. You can also ask us to use Special definitions - Eurostat or OECD definitions for example. We can always work with you.
What is the problem with Metropolitan Area definitions?
They include multiple cities in many cases. This means you are actually including neighbouring cities, and sometimes they have strange boundaries. They often don't represent a behavioral understanding of cities.
Is there any price difference?
Metropolitan Area (MSA) definitions are more expensive than Urban as in some cases we are combining 2-5 (or more) city centers per MSA.
How do you find your data?
We consult over 20,000 sources and have access to unique data mining techniques and proprietary algorithms, and data tools.
What sort of data tools do you use?
Many are low-tech some are high-tech. We have a series of 12 super powers as we call them that make 2thinknow.
How experienced are your data analysts?
Our Director has 20,000 hours experience in data for 500 organizations. It takes 4 years+ intense data work at 2thinknow to become a senior data analyst. By this stage analysts have worked on 50+ external and many internal projects.
What degrees do your analysts have?
Typically Masters in IT, Business, Commerce and Analysis from a major Western university.
How are data points priced?
They are priced by unit and volume. ie. each data point has a unit price per data point.
How is a final price worked out?
Take the number of cities and multiply it by the number of data points.
i.e. 10 cities X 2 data points is 20 units.
Why are there minimum number of cities?
Minimum number of cities are required due to the work required to design, check and validate your files. This ensures we can deliver data in a timely fashion and provide support in our business model.
Where can I find current pricing details for data points?
Right here.
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