Business intelligence (BI) is a natural fit for mobile devices. More organizations are considering mobile BI not just for executives, but for a variety of workers who need access to data when not at their seats. The technology and devices have evolved to make mobile BI cost-effective to deploy—better smartphones, new tablets and faster networks have all changed the game for mobile programs. Yet, many challenges remain around architecting, implementing and managing programs successfully. 

Wayne Eckerson has written a nice guide about mobile BI. See: http://bit.ly/pQq6yM

• Is mobile BI right for your company?
  
• Which mobile BI device is right for your company?
  
• What types of employees, tasks and tools are suited for mobile BI programs.
  
• Evaluate which mobile BI architecture is a fit for your organization.
  
• Determine which mobile device types your organization should support.
  
• Role of mobile data management software.
• Architecting for mobile BI.
  

A Complete Primer to Mobile BI

Summary

Deploying mobile BI in a fast-changing, heterogeneous mobile device market is challenging. The first step is to acknowledge that you will have to support multiple mobile operating systems and run your BI applications on employee-owned devices. The second is to invest in MDM software to manage the distribution, management, security and troubleshooting of those devices and your BI application. 

It’s likely that the future of mobile BI is some form of distributed computing that leverages processing power 
on the mobile device and remote servers. To compete effectively in the marketplace, mobile BI vendors are 
quickly embracing hybrid architectures to deliver the best of localized and centralized computing with few of the 
downsides. But we are still in the early stages in the evolution of mobile BI architectures. Hybrid technology is still 
maturing and not broadly deployed across all mobile operating systems and devices. So, it behooves your BI 
team to carefully evaluate a proposed mobile BI offering and understand its underlying architecture and roadmap 
for development. 

Your vendor’s architectural choice will have a significant ramification on the level of user adoption for the new mobile BI applications and the amount of internal resources you need to allocate to the effort.

The success of your IT infrastructure depends upon your operating system selection and has long-term consequences.

You must factor both technical and business features and determine which ones offer your business increased performance, availability and flexibility for both current and future business requirements.

There are many excellent operating systems to chose from including (but not limited to): 

• Linux (Fedora/RedHat/CentOS/Ubuntu/Debian)
• IBM
• Unix
• HP
• Novell
• Microsoft Windows Server 
• SAP 
• Apple Mac OSX
• Oracle/Sun Solaris

Business requirements for an IT infrastructure are all about the applications. Businesses depend on their applications for themselves and their customers. The applications’ performance and availability, in turn, depend on the platform on which they are deployed. Other business requirements, such as performance (often defined as response time, reliability, and stability), availability, scalability, security, and total cost of ownership (TCO) are also of high priority in decision-making. 

More abstract requirements, like openness, reputation of the vendor, and the probability of the vendor ending product support, are often not normally specified, but play an important role in making long-term platform decisions.
Key factors that influence operating system choice

• Availability and scalability
• Application migration considerations
• Performance tools

The enterprise business requirements determine the operational requirements for the IT infrastructure, which, in turn, defines the requirements regarding reliability, availability, and supportability. Many of these operational requirements translate into technical feature requirements of available products and drive the decision of which combination of products provides the best fit for the needs of present and the foreseeable future. 

Typically, the solution that fulfills these business requirements consists of multiple components:

• hardware
• operating system
• middleware
• applications

All of these components must work seamlessly together.

Cloud definition: 

The cloud is a way of delivering IT services as an integrated solution for specific problems in an automated manner; it uses the underlying virtualization of the infrastructure so that applications are ‘abstracted’ from the hardware that processes the data. In this way, technology enabled services can be provisioned (or even self-provisioned) on an on-demand basis (often from a Web-based interface) while optimizing the infrastructure utilization that is made possible by the pooling of hardware resources.

Although this is not a perfect definition (in that it is not exhaustive), it provides a basis for then distinguishing private, shared and public clouds as well as understanding the differences between software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS).

Private Cloud definition:   the deployment of IT services inside enterprise boundaries and firewalls.

The following fast and scalable databases should be considered as an alternative to SQL for the right project:

• Cassandra
  
• CouchDB
  
• MongoDB
  
• Redis
  
• Riak
  
• Neo4J
  
• FlockDB
  

Some of these new databases are quite sophisticated, while others are deliberately bare bones. But they are fast and scalable.  All of the packages are relatively stable and useful -- for the right projects. But none of them are as feature-rich or sophisticated as the best commercial SQL tools.

These new databases are different than traditional relational databases following ACID rules that converged on a set of features and a standard language. They appear to take basic pairs of keys and values, but they're tuned for different use cases. The major variations aren't in the format of the data but in how often it's replicated, cached, and sharded.

The advantage is if the specific project needs fit the abilities of one of the new databases. If they line up well, the performance boosts can be incredible because the project developers aren't striving to build one Dreadnought to solve every problem.

The downside is a lack of interchangeability at this time (will change in future). Switching is more difficult than it is with the SQL databases. There's no standard query language, nor is there a vast array of abstraction layers like the JDBC. 

Summary:

Cassandra

Facebook needed something fast and cheap to handle the billions of status updates, so it started this project and eventually moved it to Apache where it's found plenty of support in many communities. It's not just for Facebook any longer. Many of the committing programmers come from other companies, and the project chair works at DataStax.com, a company devoted to providing commercial support for Cassandra.The heritage of the Cassandra project is obvious because it's a good tool for tracking lots of data, such as status updates at Facebook. The tool helps create a network of computers that all carry the same data. Each machine is meant to be equal to the others, and all of them should end up being consistent once the data propagates around the P2P network of nodes, though it's not guaranteed. 

The key phrase is "eventual consistency," not "perfect consistency." If you've watched your status updates disappear and reappear on Facebook, you'll understand what this means.The tool runs in Java as a separate process waiting for interaction. There's already a collection of higher-level libraries for Java, Python, Ruby, and PHP, as well as some of the other languages.Using Cassandra seems relatively simple, but I still found myself getting hung up on several barriers, such as defining a keyspace (which acts as a namespace but for the columns). Getting up to speed takes more than a few minutes because there are more than just the basic routines for storing collections of values. Cassandra is happy with a sparse matrix where each row stores only a few standard columns, and it builds the indices with this in mind.

Much of the complexity in the API is devoted to controlling just how quickly the cluster of nodes moves toward consistency. You can specify the speed of synchronization for columns and collections of values called supercolumns.Getting everything running is now fairly well documented, but getting it running quickly requires a fair amount of both hardware and operating system tuning. The biggest bottleneck is the commit log. Optimizing the way that this is written to disk is the most important part of improving writes. Speeding up the extraction of data involves paying attention to the pattern of reads. Did your old, fancy database do this for you fairly automatically? Ah, don't complain. It's fun to think about the hardware and how it affects your software.

CouchDBCouchDB stores documents, each of which is made up of a set of pairs that link key with a value. The most radical change is in the query. Instead of some basic query structure that's pretty similar to SQL, CouchDB searches for documents with two functions to map and reduce the data. One formats the document, and the other makes a decision about what to include.I'm guessing that a solid Oracle jockey with a good knowledge of stored procedures does pretty much the same thing. Nevertheless, the map and reduce structure should be eye-opening for the basic programmer. Suddenly a client-side AJAX developer can write a fairly complicated search procedure that can encode some sophisticated logic.

The core of CouchDB is written in Erlang, but the API and interface is all JavaScript or JSON. You won't need to worry about this detail. The JavaScript API only enhances CouchDB's appeal for the average Web developer who can store documents and even entire websites inside the database itself.There's a burgeoning community growing around CouchDB. All of the major languages now have client libraries that simplify the interaction with the database and make it possible to store your data. They don't always expose all of the power of the query function, but that's not necessary for every service. There are also companies like Couchbase that bundle CouchDB into commercial product offerings. Cloudant offers the database as a hosted service and partners with companies like CloudBees to support the code running on the Cloudant cloud. It's getting easier and easier to use CouchDB like a service.

MongoDB

MongoDB is just one of the examples of how JavaScript is taking over the world. The program takes data formatted as JavaScript objects (a format known as JSON) and stores them away. Queries are basic JavaScript functions. It's not much different from using the console of your browser.Well, that's simplifying things a bit. The big difference is that MongoDB will create indices for the columns of your database and return queries faster when the indices are correctly constructed. That's part of your job, by the way. You want to anticipate which indices your users will need.You don't need to speak the subset of JavaScript for this language because there's a big collection of libraries and drivers written for all of the major languages and many of the minor ones. 

These libraries are extensive, and some of the major languages have extra layers that wrap and unwrap objects when storing and retrieving them.There's also a fair number of extra tools for working with the database. PHPMoAdmin, a cousin of the MySQL tool PHPMyAdmin, is just one of almost a dozen tools for admins. The proliferation of these tools is gradually erasing one of the standard reasons for sticking with a classic database. As I found more of them, I noticed that everything was more comfortable.

Redis

Like CouchDB and MongoDB, Redis stores documents or rows made up of key-value pairs. Unlike the rest of the NoSQL world, it stores more than just strings or numbers in the value. It will also include sorted and unsorted sets of strings as a value linked to a key, a feature that lets it offer some sophisticated set operations to the user. There's no need for the client to download data to compute the intersection when Redis can do it at the server.This approach leads to some simple structures without much coding. Luke Melia tracked the visitors on his website by building a new set every minute. The union of the last five sets defined those who were "online" at that moment. The intersection of this union with a friends list produced the list of online friends. These sorts of set operations have many applications, and the Redis crowd is discovering just how powerful they can be.Redis is also known for keeping the data in memory and only writing out the list of changes every once and a bit. Some don't even call it a database, preferring instead to focus on the positive by labeling it a powerful in-memory cache that also writes to disk. 

Traditional databases are slower because they wait until the disk gets the information before signaling that everything is OK. Redis waits only until the data is in memory, something that's obviously faster but potentially dangerous if the power fades at the wrong moment.The project leaders are still exploring how to expand the project, an intriguing decision because there's more than one official version of Redis from the main team. There's even one official build of Redis that comes with a Lua interpreter and a disclaimer saying that "there is no guarantee that scripting works correctly or that it will be merged into future versions of Redis!" Projects like these are never boring.Redis providers are starting to appear. OpenRedis promises it's "launching soon." Meanwhile, Redis Straight Up charges just $19 per month, plus all of the costs from Amazon's cloud. The service handles the configuration and passes the costs on to you.

Riak

Riak is one of the more sophisticated data stores. It offers most of the features found in others, then adds more control over duplication. Although the basic structure stores pairs of keys and values, the options for retrieving them and guaranteeing their consistency are quite rich.The write operations, for instance, can include a parameter that asks Riak to confirm when the data has been propagated successfully to any number of the machines in the cluster. If you don't want to trust just one machine, you can ask it to wait until 2, 3, or 54 machines have written the data before sending the acknowledgment. This is why the team likes to toss around its slogan: "Eventual consistency is no excuse for losing data."The data itself is not just written to disk. Well, that is one of the options, but it's not the main one. Riak uses a pluggable storage engine (Bitcask by default) that writes the data to disk in its own internal format. 

There are several other options, including a version of InnoDB for those who are nostalgic for MySQL. You can get all of the belts and suspenders with the clustering power of Riak.When it comes time to fetch the data, Riak offers to eliminate any of the errors that might appear. If two nodes end up with different versions of an object, Riak can either choose the youngest update or return both of the objects and leave the decision up to your client code. This is a very useful option for detecting potential errors in the data.There are a large number of query options. The basic architecture is map and reduce, but there is also the chance to write the functions in either Erlang or JavaScript.The project is shepherded by Basho, a company that provides both open source and enterprise versions of Riak. The open source version appears quite feature-rich. The main differences in the enterprise version are a slicker Web-based administration tool and the availability of high-speed, internode communication across data centers. And only the enterprise version can use SNMP.

Neo4J

If there's one application that's most different in this collection, it's Neo4J, a tool optimized to store graphs instead of data. The Neo4J folks use the word "graph" like a computer scientist to mean a network of nodes and connections. Neo4J lets you fill up the data store with nodes and then add links between the nodes that mean things. Social networking applications are its strength.The code base comes with a number of common graph algorithms already implemented. If you want to find the shortest path between two people -- which you might for a site like LinkedIn -- then the algorithms are waiting for you.Neo4J is pretty new, and the developers are still uncovering better algorithms. In one recent version, they bragged about a new caching strategy: searching algorithms will run much faster because Neo4J is now caching the node information.

They've also added a new query language with pattern matching that looks a bit like XSL. You can search a graph until you identify nodes with the right type of data. It is a new syntax to learn.The Neo4J project is backed by Neo Technology, which offers commercial versions of the database with more sophisticated monitoring, fail-over, and backup features.

FlockDB

If someone out there is writing code, someone else out there is complaining that the code is too complicated. It should be no surprise that some people think Neo4J is too intricate and sophisticated for what needs to be done. We know that Neo4J has truly arrived because the FlockDB fans are clucking about how FlockDB is simpler and faster.FlockDB is a core part of the Twitter infrastructure. It was released by Twitter more than a year ago as an open source project under the Apache license. If you want to build your own Twitter, you can also download Gizzard, a tool for sharding data across multiple instances of Flock. Both tools are ready and waiting to run in a JVM.Although many of us would call FlockDB a graph database because it stores relationships between nodes, some think that the term should apply only to sophisticated tools like Neo4J. Did someone start following someone else? Well, you can link up Flock's nodes with data such as the time that the relationship began. That part is like Neo4J. Where Flock differs is how deeply you can query this data. 

FlockDB takes a pair of nodes and gives you the data about the connection. Everything else is up to you. Neo4J not only enables all types of graph-walking algorithms, but it provides them as services. FlockDB uses the word "non-goal" for these multihop queries, meaning that the developers have no interest in supporting them.The code is pretty new, and it doesn't seem to be attracting the same kind of widespread attention as some of the other projects. All of the recent commits have come from Twitter employees, and I wasn't able to find anyone offering FlockDB hosting as a service. FlockDB still seems to be mainly a Twitter project.

How do you choose?

There's no easy answer. Most shops would be happy with any of them, even if they select the worst one for their needs. Choosing the best, though, is a bit harder because a good developer will want to balance the strength of the project, the availability of commercial support, and the quality of the documentation with the quality of the code.The greatest divergence is in the extras. All of them will store piles of keys with their values, but the real question is how well they split the load across servers and how well they propagate changes across them. 

Then there's the question of hosting. The idea of a cloud service that will do all of the maintenance for you is seductive.The stakes are higher because switching is more difficult than it is with the SQL databases. There's no standard query language in this world, nor is there a vast array of abstraction layers like the JDBC. 

These NoSQL databases have the power to lock you in. That's the price for all of the fun and features.

U.K. government policy makers will be able to work securely on classified documents across departments for the first time thanks to a deal with cloud computing and content management service provider Huddle.

David Williams, Operations Director of FCO Services, the branch of the U.K. government that runs the network, said the decision to chose Huddle was driven by two things: efficiency savings and the improvements to collaboration it would deliver.

Some 70% of government departments have been using a version of Huddle for some time, said Mr. Mitchell, but anything with a classification of “restricted” or above was prohibited. So the government commissioned a special secure version, called Huddle IL3, to allow it to handle more sensitive documents up to restricted level. According to a government spokeswoman a large amount of government work is done at the restricted level.

Cloud-based solutions get round the problem of having multiple versions of documents stored on individual computers. They also help tackle the issue of users, when faced with obtrusive security procedures, using their insecure Gmail or Hotmail accounts.

Surely London-based Huddle has just made itself a target for every hacker in the world wanting to crack into the U.K. government’s secrets? Not so. “It is running on the government secure intranet on their servers in their data center” said Mr. Mitchell.

He added that because they were running on the government servers, they were in theory authorized to work to higher levels. He said they were hopeful to be cleared to handle the next level of security, confidential (IL4), next year.


See: http://tinyurl.com/3w8eh69

See: http://bit.ly/nDyMF3

September 21, 22 and 23 in Denver, Colorado.

Learn skills needed to implement a new ERP system. Hosted by Eric Kimberling, president and chairman of Panorama Consulting Solutions, this interactive seminar series focuses on all the steps necessary to:

Select the right ERP software for your company

Negotiate with vendors

Document business processes to increase ROI

Implement with aplomb

Build business blueprints

Manage and train staff

Succeed!

Attendees will benefit from independent industry expertise gleaned over hundreds of ERP implementations from hundreds of ERP software vendors. Topics to discuss include:

Overview of common ERP implementation challenges and obstacles

Fundamentals of ERP implementation project management

Deep dive analysis of ERP implementation benchmarks and best practices

Implementation lessons learned from ERP implementation failures and lawsuits

The benefits and drawbacks of cutting-edge ERP options, including cloud ERP and software as a service (SAAS) ERP

See Agenda: http://tinyurl.com/3fw3ncy

The BI & Analytics Perspectives 2011 conference features sessions that go beyond examples of basic Business Intelligence to discussions on predictive analytics and the challenges of harnessing the power of Big Data and Mobile BI. This year’s program will show you how to move your organization from here to “what’s next” in the world of BI strategies and practical techniques for analytics.

1. IBM delivers the Industry Keynote on the latest trends and IBM’s vision and roadmap for the coming business cycles
2. Doug Porter, SVP & CIO , Blue Cross/Blue Shield Association and Swati Abbott, CEO, Blue Health Intelligence discuss “ Using Predictive Analytics to Build a World Class Healthcare System”
3. CIO 100 Winner, Mark Stone, SVP & CIO, Safety-Kleen Systems, Inc., discusses "The CIO as Innovator: Providing Rich Business Intelligence on a Poor Man's Budget" 
 Topics to be covered include:

• Building a strategy for harnessing the growth and tackling the challenge of Big Data
• More effectively leveraging social media data to enable real time decisions
• The consumerization of IT: integrating Mobile BI and aligning BI assets to grow the business
• Using BI for collaborative decision making across the enterprise
• BI in the Cloud: Integrating on premise and cloud-based analytics