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YOU Don’t need BIG Data?

Business Reports

I Constantly hear people say

Business Reports

Business Intelligence

Our database is less than a terabyte. Big data SIMPLY isn’t for us

You might be right?

However, before you jump to that conclusion, I have a few questions for you to consider?

  • Do you collaborate with partners, suppliers?
  • Do you use open source data? For example, government, NGO’s, commercial, databases.
  • What about social media?​
  • What about data from sensors or machines?
  • Do you have offices, overseas?​​
  • Would the ability to be able to identify areas in the world susceptible to political, economic instability prior to such conditions becoming a serious issue to trade, be beneficial to you?

Obviously the answer is yes.

If you were able to Answer YES to some or all of the questions above, then BIG DATA is for YOU.

Perhaps weather patterns affect demand for your product service offering?

Being forewarned might help you with inventory planning?

An example of this is a retailer matches weather patterns to purchases. Using such data, you just might find a real gem. Data patterns may clearly illustrate, particularly weather conditions, leads to explosive demand for a specific item. You may also find moving slower selling items next to explosive demand items increases your sales for these slow shifting higher profit items.

Social media

Possibly you want to know what your customers are saying, feeling about your product service offering?

For good or bad you need to pull the data into your system and once there you need to analysis the data.

Think about this way. You start an advertisement campaign only to discover a few months into the campaign the results aren’t quite what you expected. Immediate feedback would have empowered you to make real time fortuitous decisions based on facts, not intuition.

Think about this way. You start an advertisement campaign only to discover a few months into the campaign the results aren’t quite what you expected. Immediate feedback would have empowered you to make real time fortuitous decisions based on facts, not intuition.

We are rapidly moving towards the INTERNET of THINGS.

Before you dismiss this factor.

If you manufacture machines and or devices then you are probably thinking about connecting such things to the internet. For example aircraft engines generates one terabyte of information an hour. Buildings, devices, cars you name it, will generate data.

Analysing this type of data correctly, could deliver a competitive advantage. Examples of this are building managers having the ability to manage power consumption, another example motor insurance companies fitting on board devices to monitor driving behaviour. The data generated is used to determine insurance premiums.

Another example, a car service. The mechanic plugins the car into a terminal. The information is sent to the manufacture. The manufacture uses the data to determine how parts are performing and this data may result in changes in manufacturing or a software updates. Yet another example, driverless cars are a very real possibility in next few years.

So as you’ve just learnt, sensor data has already become a reality for us all, and this will only increase.

What I’m trying to state is, increasingly, your internal databases, CRM, Accounting, blogs, social media, analytics, data warehousing aren’t your only concern. Competitive advantage necessitates interaction with external data sources.

So the final question has to be:

ARE competitors stealing an advantage by finding these hidden data gems?

Google records EVERTHING you look for

Big Data

Good or bad you may be surprised to learn Google makes some of this data available to you and I!

So with total abandonment, let’s explore all this lovely data.

So let’s begin at the beginning?

We start by using a website called Google Trends.

To be able to make use of this service you really need a Google account.

If you don’t have one, you can sign up for free account, by clicking here...

Your browser choice is entirely your own but why not use Chrome for this exercise.

Using your preferred browser, in the address bar type https://www.google.com/trends/ The site will enable you and I, to learn what other people are looking for on Google and how frequently they do so.

Recently England hosted the Rugby World Cup and this was reported as being a success for all. So let’s investigate the supposition.

Begin by typing the term “2015 Rugby World Cup” then press the enter key or click the search button.

Reviewing the regional interest section, I was surprised to learn Fiji leads global interest in rugby, ahead of New Zealand. I was shocked and surprised to learn England wasn’t even listed.

Use Google Trends to learn what people are looking for.

Let’s enter another search term, this time “Winter” and below the “Worldwide” search field select the UK.

It’s not surprising the search term “Winter” begins to increase from August onwards and declines in April.

If you choose a southern hemisphere country, the results are reversed. Scroll down to see related searches.

You can run searches to find out which sports are popular in which countries.

Just add a comma between each sport for example “soccer, cricket, rugby, snooker”. Question the returns, do you think there is a pattern, does the country have an imperial past and has that influenced their sporting interests.

Men are from Mars and woman are from Venus?

Click to Tweet

Men are from Mars and woman are from Venus?

Obviously the answer is NO.

But are there any differences in the way people choose presents for their partners?

To make it interesting conduct a worldwide search by typing in “gift for men, gift for woman” and then “gift for boyfriend, gift for girlfriend” then “gift for husband, gift for wife”.

Look at country differences and investigate what occurs when the term changes gift for men and gift for woman then search for gift boyfriend and gift girlfriend.

Change the time period to compare changes.

  • Try the last twelve months.
  • Last ninety days the last hour.

Assuming you wish to manipulate the data further using Excel or spreadsheet application download the CSV file. To do this Google requires you to have an account. Once logged in you will be able to download the CSV file.

There are other resources for example Wikipedia. Visit http://stats.grok.se/ and in article name box type “Christmas”, “Bank of England” try changing the time period.

If you are interested in investigating the surges in Wikipedia Bank of England article, try searching for corresponding time period by visiting online newspapers, broadcasters’ website for example BBC business section reports.

Well done, if you’ve read this far. My very hearty congratulations.

Why not spend a few minutes investigating what else is out there for FREE.

The Power of BIG DATA

Data forecast the future

A really good illustration of the Power of BIG DATA by the Epc Group

What's impressive when you use Office 365 and Power BI, you don't need a data analyst.

Christopher Bird
MS BI Consultant             

Power your business ahead of your competitors with free open data

Data Insight


Data Insight

Business Reports

Huge comprehensive and accurate data sets covering a wide range of topics held by public bodies and large companies can be used to MAKE MONEY.

It’s not just for the tech savvy wanting to create a hot new app either.

OPEN DATA can become an integral part in IMPROVING business intelligence, planning and research.

Here’s an introductory guide to structuring a plan and cherry picking the best of what’s available online.

Your first step, RESEARCH

Your biggest challenge will be DEFINING your QUESTIONS.

To help you to define what you need to focus upon begin by asking and answering questions. Talk to your staff, your customers or clients and seek to understand your competition.

Continue reading

I can predict the future!

Forecasting the future


I use Business Intelligence  (BI) software tools.

BI uses data to answer questions a business decision maker wants answered. 

Ever conscious minute of the day or night we all make bad or good decisions about what is about to happen.

I should say we attempt to predict what others are likely to do based upon what we think we have identified as repeating patterns of behaviour.

For example, the Los Angeles police department are using data to predict where crimes are likely to happen with the intention of either preventing or arresting the perpetrators. The police achieve this by analysing very large data sets to reveal patterns of behaviour.

Think of it this way

Individually we are likely to know how members of the family or friends are likely to behave in a given situation.

For example, a husband takes his wife out to dinner. He thinks if he tells her the table is booked for 7:30 she is likely to be ready to leave their home around 7:30 as she always takes’ her time when preparing herself to go out for the evening.

To prevent arguments, he books the table for 8:30. He knows if they leave at 7:30 they will be sufficiently time to travel to the restaurant. His wife knows his pattern of behaviour so she chooses to not hurry herself.

Predicting human behaviour can make you MONEY.

Humans tend to be rather good at predicting behaviour when individuals know each other. However, we are far less effective when making sense of people we do not know or when analysing large data sets.

Real World examples

Professor Hans Rosling's, Gap Minder organisation collaborating with the Open University and the BBC made a series of very entertaining ‘Don’t panic themed programs illustrating how data can be used to predict the future by identifying repeating behavioural patterns. If you haven’t seen these programs I recommend you do. Click here...

Sharad Goel and colleagues put forward a hypothesis that we seek information online to aid decision making.

For example, we research films we may like to see and possibly restaurants we might choose to visit afterwards. Goel et al. viewed internet data such as films, songs, and games people had been looking for online and showed the data could forecast the rankings and revenues of films, songs, and games the following week. If you use the search data to build a predictive data model, it’s possible to improve predictions as to which bars, hotels and restaurants are going to be popular the next week.