Archive for the ‘open source’ Category
These are the main points from The Data Explosion section of my Next Big Thing In Big Data presentation.
- The data explosion started in the 1960s
- Hard drive sizes double every 2 years
- Data expands to fill the space available
- Most data types have a natural maximum granularity
- We are reaching the natural limit for color, images, sound and dates
- Business data also has a natural limit
- Organizations are jumping from transactional level data to the natural maximum in one implementation
- As an organization implements a big data system, the volume of its stored data “pops”
- Few companies are popping so far
- The explosion of hype exceeds the data explosion
- The server, memory, storage, and processor vendors do not show a data explosion happening
- The underlying trend is an explosion itself
- The explosion on the explosion is only minor so far
- Popcorn Effect – it will continue to grow
Please comment or ask questions
Dan Woods put out a nice piece yesterday on his Forbes blog titled “Lessons From The First Wave Of Hadoop Adoption“.
I agree with him that the insights and advantages of Big Data solutions need to be described in ways other than technology. I’m going to add on to his insights.
1. It’s about more than big data. It’s a new platform.
Yes, it is a new platform. That means it’s different than the old ones. The fact that you can do some things cheaper than you could before is not the main idea. A bigger story is that some things that were economically not possible before, now are. But the main idea is that this is a new platform, with new capabilities, that needs to fit into your existing data architecture.
2. Don’t get rid of your data warehouse
I completely agree. Big Data technology is a new tool with new characteristics. Using it to replace a Data Warehouse technology that is finely tuned for that use case is not a great idea. Don’t listen to the “Hadoop will replace every database within x years” crowd. No database has managed to replace every database. No database ever will because the variety of the use cases is too large.
3. Think about your data supply chain
Since a Big Data system needs to fit in with everything you currently have and operate, integration is a significant priority. Understand that with Big Data you can build a Big Silo, but a Big Silo is as bad as a small silo (just a lot bigger). You should not be required to pump all your data from every system into Hadoop to get value from it. Design you data architecture carefully, the implications and fallout of getting it right or wrong are significant.
4. It’s complicated
Yes it is. It’s also not cheap to do it well. Sure you can download a lot of open source software and prototype or prove your ideas without a lot of upfront outlay. But putting it into production is a production. Expect that.
“Dixon’s Union of the State idea gives the Data Lake idea a positive mission besides storing more data for less money,”
“Providing the equivalent of a rewind, pause, forward remote control on the state of your business makes it affordable to answer many questions that are currently too expensive to tackle. Remember, you don’t have to implement this vision for all data for it to provide a new platform to answer difficult questions with minimal effort.”
- Let the application store it’s current state in a relational or No-SQL repository. Don’t affect the operation of the operational system.
- Log all events and state changes that occur within the application. This is the tricky part unless it is an in-house application. It would be best if these events and state changes were logged in real time, but this is sometimes not ideal. Maybe SalesForces or SugarCRM will offer this level of logging as a feature. Dump this data into a Data Lake using a suitable storage and processing technology such as Hadoop.
- Provide the ability to rewind the state of any and all attributes by parallel processing of the logs.
- Provide the facilities listed above using technologies appropriate of each use case (using the rewind capability).
The plumbing and architecture for this is not simple and Dan Woods points out that there are databases like Datomic that provide capabilities for storing and querying state over time. But a solution based on a Data Lake has the same price, scalability, and architectural attributes as other big data systems.
ZDNet reports on a Forrester survey that finds 5 out of 6 developers are using or deploying open source.
In the survey they found that 7% of developers are using open source software tools such as Pentaho.
The United States Department of Labor state that, in 2010, there were 913,100 software developers in the USA alone.
7% of 913,100 means about 64,000 developers using open source business intelligence software. Nice.
My thoughts on the whole Emily White/stealing music topic:
When she says she only bought 15 albums, I think she is talking about physical CDs. I think she did buy some of her music online. But she clearly states that she ripped music from the radio station and swapped mix CDs with her friends, and she makes it sound like she thinks this is not stealing.
Don’t Blame iTunes
Many people who complain about artist’s income people blame Apple and iTunes. Yes, iTunes propagated the old economic splits and percentages into the digital world. But Apple did not create those splits, they were agreed upon in contracts between the labels/producers and the artists. What iTunes did was to provide an alternative digital distribution medium to Napster. Apple saved artists from the prospect of getting no revenue at all. People who attack and boycott iTunes thinking that they are helping artists are deluded.
It’s Not Just Music
This whole debate also extends to movies, books, news commentary, and software – anything that can be digitally copied. In each of these arenas, the players and economic distribution is different, but the consequence of not paying is the same. If we all behaved this way, ultimately, there would be no books, or movies either. So how does this relate to proprietary software, open source software, and free software?
Just like companies that publish books, music, movies etc, proprietary software companies were the gatekeepers. They decided what software was created and made available. When the hardware and software becomes available at the consumer level, independent producers spring up. This happened with freeware software for PCs. The internet enables the distribution of the software, and methods of collecting payment. The costs of creating books, music, and movies have dropped dramatically because of the hardware and software now available. But, if no-one pays for the content created the proprietary software companies will go out of business.
Open source and free software are other ways for creating and distributing software, the difference being that these rely on software (source and binaries) being easy to copy. Don’t steal Microsoft’s BI software and use it without permission. Use our open source BI software – we want you to.
Free software requires that the software, and all software that is built upon it, be ‘free’. In this case ‘free’ means you can freely modify it, distribute it, and build upon it, and you give others those same rights. You can still charge for the software, but it makes no sense to (given the rights you give to your ‘customer’).
The ideals of Free Software Foundation (FSF) are based on the notion that when you think of something or invent something, it belongs to the world, you don’t own it. This is a wonderful idea, however most of the world, including many industries,and jobs, and professions, are based on the opposite principle – if you create it, you own it. To my mind I have fewer rights under the FSF view of the world, I don’t have the right to my own ideas.
Because of the freedoms that the Free Software Foundation believe in, they are against Digital Rights Management (DRM) software. DRM tries to protect the rights of artists, producers, and distributors of artistic content. In order to protect these rights, software is needed that is proprietary. If the DRM source code was open, it would make it easy for hackers to decode the content and remove the copy protection. So the Free Software Foundation is taking up the fight against DRM, calling it ‘Digital Restrictions Management’ (http://www.fsf.org/campaigns/drm.html). They call it this because, they say, DRM takes away your right to steal other people’s inventions. If you support of DRM-free software, you are choosing to fight against musicians, authors, actors.
The Open Source movement takes a pragmatic approach on this topic. When you have an idea, it is yours. You can choose to do whatever you want with your invention. If it is a software invention, and you choose to put it into open source, that’s great. If you choose not too, that’s fine too, because it is yours. Open Source allows hybrid models – where a producer can decide to put some of their software into open source but not all of it (open core or freemium model). This model enables a software producer to provide something of value to people who would not have paid for anything anyway (this includes geographies and economies where the producer would not sell anyway). These people are willing participants and contributors in other ways. The producer also gets to sell whatever software products it wants.
For some creative areas, if no-one pays for any content anymore, the creators will disappear eventually, and there will be no more content. But what happens if no-one pays for software anymore?
Proprietary software dies eventually, unless they switch to services models.
The majority of people contributing to open source/free software today are IT developers. There are two main types here: creating/extending/fixing software in the course of getting their project finished, or sponsored contributors. IT is where the majority of software developers are today, so IT/enterprise/business software is safe.
The software that would be at most risk would be software that is created by smaller software companies. Particularly software that has large up-front development costs. Games. The first, and maybe only, software segment to die would be the big-budget, realistic, immersive, loud video games. Who cares most about these games? The same demographic that is stealing all the music.
I say let Generation OMG copy and steal everything they want. All the really cool and fun careers will evaporate. Lots of the stuff they love (movies, music, games) will disappear. After they have spent a decade texting each other about how sucky everything is, they will grow up and have to re-create these industries. Hopefully with better economic structures than the current ones.
We announced a strategic partnership with DataStax today: http://www.pentaho.com/press-room/releases/datastax-and-pentaho-jointly-deliver-complete-analytics-solution-for-apache-cassandra/
DataStax provides products and services for the popular Apache No-SQL database Cassandra. We are releasing our first round of Cassandra integration in our next major release and you can download it today (see below).
Our Cassandra integration includes open source data integration steps to read from, and write to Cassandra. So you can integrate Cassandra into your data architecture using Pentaho Data Integration/Kettle and avoid creating a Big Silo – all with a nice drag/drop graphical UI. Since our tools are integrated, you can create desktop and web-based reports directly on top of Cassandra. You can also use our tools to extract and aggregate data into a datamart for interactive exploration and analysis. We are demoing these capabilities at the Strata conference in Santa Clara this week.
- Product downloads, how-to videos and documents are available at http://www.pentaho.com/cassandra and http://www.datastax.com/pentaho
- Attend the webinar on March 15th to learn more and about using Cassandra’s integration with Pentaho Kettle http://www.pentaho.com/datastax-webinar
- Download, access how-to documents and videos at http://community.pentaho.com/BigData
This week at Pentaho we announced a major Big Data release, including:
- Open sourcing of our of big data code
- Moving Pentaho Data Integration to the Apache license
- Support for Hbase, Cassandra, MongoDB, Hadapt
- And numerous functionality and performance improvements
What does this mean for the Big Data market, for Pentaho, and for everyone else?
We believe you should use the best tool for each job. For example you should use Hadoop or a NoSQL database where those technologies suit your purposes, and use a high performance columnar database for the use cases they are suited to. Your organization probably has applications that use traditional databases, and likely has a hosted application or two as well. Like it or not, if you have a single employee that has a spreadsheet on their laptop, you have a data architecture that includes flat files. So every data architecture is a hybrid environment to some extent. To solve the requirements of your business, your IT group probably has to move/merge/transform data between these data stores. You may have an application or two that has no external inputs or outputs, and no integration points with other applications. There is a word for these applications – silos. Silos are bad. Big data is no different. A big data store that is not integrated with your data architecture is a Big Silo. Big Silos are just as bad as regular silos, only bigger.
So when you add a big data technology to your organization, you don’t want it to be a silo. The big data capabilities of Pentaho Data Integration enable you to integrate your big data store into the rest of your data architecture. If you are using any of the big data technologies we support you can move data into, and out of these data stores using a graphical environment. Our data integration capabilities also extend to traditional databases, columnar databases, flat files, web services, hosted applications and more. So you can easily integrate your big data application into the rest of your data architecture. This means your big data store is not a silo.
For Pentaho, the big data arena is a strategic one. These are new technologies and architectures so all the players in this space are starting from the same place. It is a great space for us because people using these technologies need tools and capabilities that are easy for us to deliver. Hadoop is especially cool because all of our tools and technologies are pure Java and are embeddable, so we can execute our engines within the data nodes and scale linearly as your data grows.
For everyone else our tools continue to provide great bang for the buck for ETL, reporting, OLAP, predictive analytics etc. Now we also lower the cost, time, and skills sets required to investigate big data solutions. For any one application you can divide the data architecture into two main segments: client data and server data. Client data includes things like flat files, mobile app data, cookie data etc. Server data includes transactional/traditional databases and big data stores. I don’t see the server-side as all or nothing. It could be all RDBMS, all big data store, 50/50, or any mix of the two. It’s like milk and coffee. You can have a glass of milk, a cup of coffee, or variations in between with different amounts of milk or coffee. So you can consider an application that only uses a traditional database today to be an application that currently utilizes 0% of its potential big data component. So every data architecture exists on this continuum, and we have great tools to help you if you want to step into the big data world.
If you want to find out more:
- Visit http://community.pentaho.com/BigData which has downloads, how-tos, and other resouces
- Connect with the community on irc.freenode.net ##pentaho;
- Join the Pentaho Big Data technical developer mailing list to be notified about future big data product updates and related events.
- Attend the techcast on Thursday February 9th to learn more about Pentaho Kettle for Big Data, watch a live demo and hear how you can get involved. Register now at http://www.pentaho.com/resources/events/20120209-pentaho-kettle-webinar/
- Hands-on training FREE for attendees at the 2012 Strata Conference in Santa Clara, California. Sign-up for our how-to training session (http://strataconf.com/strata2012) on February 28th during the ‘Tuesday Tutorials.’ Register with Pentaho’s 20 percent discount code: str12sd20 <https://en.oreilly.com/strata2012/public/register> .