IKEA is a huge success story and has been a clear game changer in the furnishing industry. I am convinced that Hadoop and its related open source data management tools will do same for the IT industry. What we have already seen are just the early stages of a huge disruption we will witness in the coming years.
My faith is based on the fact that this ecosystem has the same advantages as IKEA has in its’ business idea, which is: “to offer a wide range of home furnishings with good design and function at prices so low that as many people as possible will be able to afford them.”
This business idea has three key components which can be translated to the IT world in the following ways.
“As many people as possible will be able to afford them” ➜ “Hadoop is a software package at such a low price that almost every company is able to afford it already”
Ikea’s idea says “…products that are affordable to the many people, not just the few”. Any average company in either the Furnishing or the IT industry tries to maximize its sales prices to as high as market competition allows. This leads to a situation where the amount of features is maximized and absolute prices are quite high. IKEA’s approach is just opposite. Features are optimized for most people and the whole value chain is aimed at lowered costs. Finally, sales price is pushed as low as possible, regardless of what the competitive situation is.
In the case of Hadoop and other open source products, the situation is even better. There does not exist a party trying to maximize sales margins for the initial purchase. These products do not even have sales prices. Companies like Hortonworks actively developing their own version of Hadoop do not ask for a price for the product itself – you can download the software from their website at any time, and there are no license restrictions forbidding its use in production environments. Their business model is to only charge for the services they provide. In the same sense, it would be like IKEA giving away their furniture for free and charging only for home delivery, assembly and warranty. Like in the case of IKEA furniture, Hadoop tools expect a more “Do-It-Yourself” attitude, but at the same time cost savings can be huge.
Naturally license costs are not the whole truth. In part two of this blog series, I will go through how you should consider things like hosting, maintenance and skill costs.
“A wide range of home furnishings” ➜ “Hadoop and other open source Big Data projects provide a huge range of IT software for areas of data management and system integration”
When you step into an IKEA store, you immediately understand that the offering is wider than in any other chain – it is huge. Similarly products under Hadoop’s umbrella cover all major aspects of traditional data warehousing and system integration. So you have a tool for almost every purpose and blueprints for how to make them communicate with each other.
Even more important than just availability of the tools, is the way it changes your thinking. As people start to master both the real-time system integration aspects and analytics, they start to realize that building automated decision making processes are a realistic goal. Automated decision making and real-time information are changing all industries at the moment. For example, at Uber there is no-one matching cars and passengers or informing both parties in real-time where the car is at each moment. Additionally, their system is even doing predictions about costs and arrival times. And this process is running simultaneously for millions of people.
In part three of this blog series, I will talk about what are some of the Hadoop and Big Data software components available and how those can do similar things for you as they are doing for Uber.
“Home furnishings with good design and function” ➜ “Hadoop tools are designed to solve issues impossible for traditional commercial tools”
For decades IT was too expensive for everyone. Roughly ten years ago internet startups started using low cost and open source software to build their services. These open source tools pretty much copied the functionalities of the commercial tools. At the high level the main difference was economics behind them. Suddenly, you didn’t need significant funding to set-up an IT company and become a millionaire.
In the shadows, these new internet companies grew faster than anyone realized. Quickly they ran into overwhelming technological challenges, which traditional enterprises and software vendors never needed to tackle. The newcomers needed to invent a way how to provide an almost 100 % automated service 24/7/365 for millions of users. If you have ever operated IT systems, you know how 99 % of CIOs would see these kind of requirements as totally impossible for their software landscape and infrastructure.
Some of the startups understood that they needed to build their own software starting from the file system, database and system integration level, in order to scale and survive. As a result, we have companies like Facebook, Yahoo, LinkedIn etc. As this software development is not their core business, they soon started to share their developments with others for free. In many ways this era of software is superior compared to traditional ones, but of course they have also some limitations.
In part four of this blog series, I will talk about what are the more detailed requirements Big Data tools were developed for. How they solve these issues and what kind of compromises you need to accept.
If you want hear more about HDP Hadoop, Modern Data Architecture and Azure Marketplace you may like these blog-posts:
Tuomas Autio: In love with Hadoop deployment automation
Mikko Mattila: Hadoop – IKEA of the IT ecosystem: Part 2
Mikko Mattila: Hadoop – IKEA of the IT ecosystem: Part 3
Mikko Mattila: Hadoop – IKEA of the IT ecosystem: Part 4