Technology

Fluent.io

Fluent.io is a new interface to mail. Think of mail as a social activity and having an interface similar to some of the social networks. The landing page is your News Feed or Stream showing all your mail in Inbox.

Fluent.io doesn’t take away any functionality of a mail client, so all labels, starring, marking as un/read still function as intended. Interestingly, Replies and forwards work similar to replying or sharing a post. So as standard, replies are at the bottom and forwards are through a drop-down menu on each item/email. The drop-down menu on each post also allows to marks it as Spam, or Un/Read and also to apply labels to it.

There is a navigation bar which shows your accounts and for each account has 6 basic menu items: Inbox, To-do list, Starred Mail, Attachments, All Mail and Labels. Two things that stand out are the to-do list and Attachments.

To-do list is exactly what it says but similar to MS Outlook, in Fluent.io mail items can be marked as to-do (or Follow-up in Outlook terms). So this is where you will see all the to-do items.

Attachments menu on the other hand is a great idea. Fluent.io collects all the attachment from all your emails and displays them under this tab. So you will see all your photos, documents, videos and other attachments here. It makes searching for attachments easy. It also provides you with a filter option on the type of attachment.

Here are some screenshots of Fluent.io: Google+

 

ScreenShots

I think this is a good start to redefining our traditional mail clients. Fluent.io currently only works with GMail and unfortunately, is not accepting any new accounts. There is a demo you can try out.

If you have come across any other mail clients which are trying to change the interface, please drop a comment below.

Have fun!

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Articles, featured

TEDx Imperial College

On 24th March 2012, Imperial College London students hosted their first TEDx event. It was my first time attending a TEDx event too! I have to say it was great fun listening to innovate new ideas. being a graduate from Imperial College, it was great to go back for the day.

The event was 6 hours long and split into 3 sections with 12 speakers. The sections were as follows: Changing Perspective, Breaking Boundaries and Improving Lives.

The first talk was presented by Manel Torres called “Spray-on Fabrics“. Manel Torres talked about his research on fabrics sprayed from a can. He has achieved this and was wearing a t-shirt that his colleagues sprayed on him.Other than the fact that the fabrics were sprayed onto the body, what was amazing was that if the fabric was cut or ripped, you can simply spray on a layer over the rip and it is mended. The dry out time is fairly quick and it doesn’t stick to skin or hair!

Next up was Nick Sireau who spoke about rare diseases and how they are fundamental to understanding some of the common diseases. He spoke at length about Alkaptonuria (AKU) and how it has no cure but advances have been made to treatments and support for the patients.

The first session ended with Andrew Morley talking about “Music from the Genome”. It was the process of taking the DNA and translating it to music; mapping the bases to musical notes and creating a choral piece.

The second session focused on breaking boundaries, but the talk by Michael Korn created  boundaries or walls. KwickScreen is a product designed by Michael which is essentially a retractable room partition. It is a portable device which creates a screen or a partition when pulled out. This has currently been used by the NHS to create partition between patient beds and sections. The idea is simple and why it works.

Alexander Schey presented Racing Green, a student team at Imperial College set out to change the electric vehicle scene. They built a fully electric car with a top speed of 200 kmph and range of 400+km on a single charge. The most impressive feat is the endurance drive on the Pan American highway from Alaska to Ushuaia about 26000km. The technology is very promising.

Aldo Faisal spoke about breaking into the brain and helping people with paralysis or some form of disability to interact with computers. He explained how the eye and it’s muscles are connected directly to the brain and so even with any spinal cord injury (which causes paralysis) , the eye can still move at will. Using this fact, he built a cheap and affordable eye tracking device allowing people to interact with the computer through simply looking at the screen and blinking.

Aleks Kolkowski played the old Victorian sounds of the Great Exhibition of 1851 through the use of wax cylinders and gramophones. Sophie Scott showed how laughter is the emotion which is shared among all cultures including the tribes of Africa who have had no contact with any other civilisation. Interestingly she states that rats “laugh” as well.

John Graham-Cumming talked about Charles Babbage and his Analytical Engine, the first computer. Interestingly, this was never finished and the design remains on paper. Now a project is under way to construct this machine and bring it to life.

Andrew Shoben is THE public art professor in the UK. His work revolves around integrating public art with the public. His art came in the form of tuned railings so when struck in order played a tune; a project in Cambridge where benches and bins were robotic so when called, they would move towards the people.

Joanis Holzigel spoke about e.quinox. A student initiative to help improve the life of villagers in remote parts of Africa by providing cheap and clean electricity. The project has already had an impact on over 2000 people in Rwanda and Tanzania. e.quinox provides battery boxes charged through solar energy and sold cheaply with LED bulbs.

Last but not the least was Junior Smart. Junior has set up a St. Giles’ trust Southwark Offenders Support (SOS) aiming to reduce re-offending by ex-offenders. He helps by providing a holistic and tailor-made support to each ex-offender in the programme. In the 5 years of running the re-offending numbers have gone down from 75% to under 10%.

 

This TEDx event at Imperial College London was a good experience in terms of learning about the new technologies,  social and entrepreneurial initiatives.

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BI

Getting started – Requirements Gathering

Every project has a circular development path.

Building a business intelligence solution is no different. You need to get the requirements of your business users, build a prototype warehouse and a cube, conduct UAT and restart the process based on the feedback.  Let’s start with he first step Requirements gathering.

The aim of this is to find out what the business users want to use the data warehouse for, what information are they after to help them in their decision-making. Find out the use cases. Start by asking them a simple question: “what do you want to get out of the solution?” This will tell you what their aim is. Now break this down into what questions they want answered trough this solution. An example could be “what is the trend of sales for item A over the last year?” This gives clues that historical trending is required, information about sales down to the level of each item sold.

Identify all the questions that need to be answered. Note down what business group each question relates to. This will help recognise the sources of data and any points of contact. Once you feel that most of the questions have been asked, start considering one business group at a time.

Each business group will have their own specific set of requirements. Think of this as building a data cube for each business group. This is the Kimball approach that was discussed in earlier post. As an analyst building a BI solution think of all the information you need and ask those questions. Dig deeper and find any more questions that the group needs answered. We need to extract what the facts or the grain need to be.

Then find out what they would like to group the data by. This will start to define the dimensions of a mart. Find out the meta data description which will help you define the data transformation rules.

The process I have described above can be broken down into 5 steps:

  1. Define Subject area and Objective
  2. Brainstorm Business Usage Scenario
  3. List business questions for each scenario
  4. Derive the measures from the business questions
  5. Determine the dimensions and build a model

If you have any questions, please post a comment below and I will try to help you out.

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featured, Photography

Long Exposure Shots using Military Shooting Techniques

A couple of weeks ago I went on a night photography tour around London with a few friends. I knew most if not all photos I will be taking would be long exposure shots. I faced a real challenge as I wasn’t armed with a tripod. I thought I would use ledges or park benches or something like that to rest my camera on for these shots. This only worked in cases where the position was right for the framing of the shot, but there was still some vibrations from the shutter clicks.

When holding the camera, I knew some basic techniques like holding my breath for a few seconds to get my body stable. This wasn’t enough even for exposure of 2 seconds. So I started researching about how to stabilise the body (mine and camera’s) for these shots.

I came across a great article written by an officer in the US Army. He details the shooting (firing) technique used for rifle shooting and how this can be applied to photography. His explanations are clear and are illustrated. There are “four fundamentals of marksmanship”: Body posture, Breathing control, Aiming and Sight, and Trigger (shutter) squeeze.

This is worth a read (link below) if you want some great long exposure shots without a tripod. Although I wouldn’t recommend a 30s exposure with this technique!

SOURCE: PentaxForums , image

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BI, Technology

Dimensional Modelling

I’m sure you have come across terms like Facts, Measures, Dimensions, Attribute hierarchies, etc. We will define these terms and see how a dimensional model is built.

A GRAIN is the smallest piece of information that needs to be presented in the warehouse solution.It is the most atomic piece of information in the data warehouse. It is best to give an example: For retail systems, a grain can be the items per transaction per customer. This is the most exact information that the warehouse will be able to provide. In defining the grain we define the fact too.

A FACT or MEASURE is something of interest. Something that we need to measure to give us an indicator to base our business decisions on. It is the most atomic piece of information used for aggregations. For example, for an inventory system this would be the items in stock; so we count (aggregate) the items to give us number of items. The fact here is an individual item, we measure the number of items. Another example can be . The piece of information of interest is customer and thus we would aggregate on this to find he number of customers enrolled or number of customers who shop at a particular store.

A DIMENSION is the information that we want to group the facts by. In the case of the inventory system, we can group the items by the type of item; eg. food, furniture, electronics, clothes, etc. For the fact customers we group them by the type of membership they hold or their city of residence. A dimension holds information related to the facts we measure.

Every dimension has attributes. The attribute usually is a property of the grouping or a sub category. For the dimension of geography, possible attributes are: continent, country, state, city. This information is grouped and described as “geography”.

This should give you an idea of what the terms mean. Once you understand these terms, you are ready to translate the business requirements into a warehouse model. In the next post we will look at requirements gathering and how to get the business users to narrow down their high level objectives.

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featured, Technology

Google Chrome (beta) for Android

Early his week Google released a beta version of their Chrome browser for Android 4.0 (Ice Cream Sandwich). You can download the beta from Android Market.

The native web browser in Android has shared the webkit with the desktop version of Chrome for a while now. The performance improvements are related to JavaScript execution and it feels well optimised for a mobile environment. The UI is very simple and similar to the desktop version. Some nice features like tab organisation are well implemented.

Instead of talking about the UI, here are some screenshots.

Try out Chrome and let me know what you think.

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BI, Business

Data Warehousing – A Process Overview

Data warehouse is a very common term that you will come across in the BI field. A data warehouse is simply a data store in its most basic definition. This data store is used for analysis and reporting and not for operational use.

The data warehouse typically has 3 layers: staging, integration and access layers. The staging layer usually contains a raw data dump from an operational database. The integration layer is where the raw data is restructured and links the data in a meaningful manner. The access layer is used for presentation and is usually for business clients.

The data warehouse stores all the business data for a corporation. This can be subdivided and stored into smaller stores known as Data Marts. Data Marts are typically subdivided by business function or logical reporting categories. If a single large Data Warehouse is implemented then this is known as centralised approach. The data is centrally stored and is accessed by all business functions. Implementing multiple data marts is a decentralised approach; as there is no single store with information from all business functions.

It’s beginning to sound like the two approaches are very different but they have a similar purpose. In fact, Ralph Kimball and Bill Inmon are the authors behind the decentralised and centralised approaches respectively. Inmon defined the idea of centralised storage and a top down approach. A top down approach starts with consideration of all the requirements at an enterprise level without breakdown by business function. Kimball defined a bottom up approach leading to decentralised storage with multiple Marts. A bottom up approach starts with individual business functions and their specific requirements. After all the marts are built these are then linked together to deliver an enterprise-wide solution.

Even though these two approaches to building a DW are different both involve 3 common stages: Integration, Analysis and Reporting. Integration and Analysis both involve manipulation of data, whereas Reporting is more about presentation of the data. It is possible to perform further analysis in the reporting layer.

The tools used for development usually support these three layers. One of the industry leading tool sets is provided by Microsoft. The SQL Server with Business Intelligence Development Studio (BIDS) supports the development of the above mentioned layers. The SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS) and SQL Server Reporting Services (SSRS) together form the MS BI stack.

SSIS is used to get data from an operational database and transform it into a dimensional or ER data store. SSAS allows building of a multi-dimensional Cube using the new DW model and perform calculations and aggregations. SSRS then allows generating reports from the Cube with some graphics.

In the next post we will take a closer look at the dimensional model (Kimball) for data warehousing and define some basic terms.

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