I have seen large organizations fail with providing successful BI services. Often the blame is on the quality of service that was provided in terms of people and technology. But dig deeper and you will see that a lack of cohesive focus is where that organization would have lost the impetus in providing the service.

One may ask what is cohesive focus. When you deal with a large organization, there are multiple processes and teams involved. There is bound to be different levels of maturity amongst the teams and this gap leads to lack of clarity and hence the lack of cohesive focus.

What are the signs of lack of focus? the warning signs will start when you see an alignment issue between the different managers in the team. The earliest warning will be when a single point of contact cannot be deployed to the project. When these signs manifest, I urge both the service provider and the customer organization to start working together at the earliest to mitigate downstream issues.  Often the damage is done by the time either organization realizes the situation.

When service providers decide to engage in program services, one word of advise, ensure that your organization is having checks and balances to avoid surprises. If you lack the desired level of maturity, ensure that you do not oversell the client expectations. Another food for thought is to develop a mutually agreed scorecard to monitor and correct course over the period of service.

No analyst organization will provide a course on how not to fail. But if you are too large or too small an organization, watch out for the lack of cohesive focus, which is your achilles heel.

Remember since this is a competitive domain, there will be no sharing of best practices or approaches. Learning from introspection is the best approach.

Companies today in all spheres from media to healthcare are struggling with the "Network Effect" phenomenon as I call it. The age of social networking has matured from zero to reality in a short span of five years, which has ushered in the "Network Effect".

What is the "Network Effect". Simply put it is the way we connect with each other as people today. One simple example is the movies, in the past few months movie producers have started looking at RSS feeds, Twitter and other social media avenues to advertise their movie and provide additional promotions to the target audience. Why?

The advent of text messages , Twitter etc have provided a channel for people to communicate their views and opinions on any subject. Such a trend has shown its impact on movies - for example last summer's release of "Transformers" did not succeed in generating interest in the young adult community as the movie did not receive rave reviews from first day or first week viewers and most had negative sentiments about the movie. On the same note, the current success of Avatar, is highly attributable to the genius of James Cameron, but the network effect of people recommending others to see the movie for its astounding technical effects and causing a mass attraction to the theaters shows the effect of "Network Effect".

We will continue to see the influence of "Network Effect" in the coming months and years. We will see in the coming days more discussions on this subject.

Year 2010 will be the year of Social Analytics in Business Intelligence. The prime reason for this thought stems from the fact that organizations have heavily invested in CRM, BI and all possible solutions to better manage themselves and their customers. But what is the use of all this data, if you cannot connect to the real world? i.e what do people talk about you, your products, services and your competition? how can you really understand the "network effect" that your customers will bring to your business?

As we move more closer to connecting the dots, the largest gap will lie in the social analytics arena. One can understand that the data volumes we are discussing is extremely large in nature, complex to process, more complex to decipher value from and extremely volatile in nature. This is exactly why I'm looking at Social Analytics being the "next BIg thing in BI".

Who are the companies that are investing into product development in this are, there are a few that come to mind, but I will hold off on revealing them in this blog.

Over the next few days, this blog will focus on this theme and expound this further.

The BI vendor market has become an imbalanced space. There is either consolidation leading to BIG behemoths or you have extremely niche startups or the last choice Open Source. What this leads to is confusion in user organizations.

With market consolidation, companies are left with a mixed bag of solutions and now need to reassess their investments, new market offerings have not reached enough maturity and open source is not accepted yet as enterprise capable in BI. Where we need to go with this situation is to setup an interoperable solution where the vendor consolidation will not impact current investments. There were third party companies that used to offer these kind of solutions and we need a new series of such technologies to be recreated.

I'm really wondering why we blame DW / BI architecture or approach as a failure, when a large portion of the silos are being built by vendor disruption in the market. I certainly hope the vendors will provide a scalable and interoperable answer in the near future.

Till we get some sensible set of solutions, we might have to live in a heterogenous world of solutins and thrive on chaos.

As we look at the last quarter of this year, a very clear subject is emerging as a contender for the "TOP" BI application in the next year. The subject is Social Applications, we are talking about Twitter, Facebook, MySpace, Sharepoint becoming a data source for the next generation of data warehouse

What are social applications? these are applications which will be developed and deployed on your existing data warehouse along with data from document/content management platforms, web forums and any textual source, sitting together with your BI applications.

It will not be a stretch to say that BI Applications will be more focused on Social Analytics. Why, because we will be chartering the space where no man has gone before i.e Textual Data of all forms structured, unstructured, semi-structured  - yes your journey into this space is a new odessey.

But the move to social applications will not be a new one. We have been scratching the surface for a decade nearly and have now succeeded in understanding how to integrate that data into the rest of the data warehouse and leverage the knwoledge embedded in the same.

Why will companies invest in social applications

•  The real customer connect will happen in this space. The new age customer maintains their web diaries about product purchase, services etc, that are shared to their social network via facebook. You need to access that indirect marketing channel
  
• If your client base blogs about your services or product and that creates a negative impact, you want to know that
• You want to see who all your competition is and what the world is saying about you vs. them
• You want to gather intelligence as much as possible on anything that you never had access to before.

These are some key drivers on why Social Applications will dominate BI as we move into the next year.

If you are an insurance company, a media or entertainment company, a video game producer or just about in any business that involves customers and interactions, you will invest into Social Applications as your BI investment

Talk about market disruption and the word Data Warehouse Appliance can replace that phrase when it comes to new technology with respect to Data Warehouses. The market of Appliance based offerings from companies old and new are making news everyday. Amidst all this noise, how do you choose the best technology?

Is it price or performance or scalability or all of these in some ratio? what factors drive your decision and what influences your decisions? To arrive at the right decision there are several factors to consider, apart from price, these a few things to consider

• Compatibility - will the platform fit into your existing enterprise
• Scalability - Can it scale to data volumes without additional hardware needs
• Maintenance - Can it be maintained with relative ease
• Usability - How usable will the solution be out of the box

Apart from these factors, you also need to think about the following

• Can it support Textual Data Integration
• Can it support GIS capabilities
• Can it support Open Source Solutions

If you take a step back and examine these points, you will begin to form your own list of features, factors and solutions and come to choose the right solution.

I'm in the process of developing a data warehouse appliance scorecard. This will be areport that will be published at this network and be available by mid-November. The goal of this report is to provide an independent analyst positioning of the DW Appliance offerings.

Over the last year we all have seen a lot of information about the data warehouse appliance. Many authors including me have written, spoken and even implemented solutions with this technology. All of a sudden the noise over the appliance market has softened. why? is the appliance concept now legacy or has the hype died? The answer is neither. Data Warehouse Appliances are being adopted mainstream more than ever before..

The data warehouse appliance market is growing more bigger and there is a serious level of maturation in the space. Companies are now considering data warehouse appliances as mainstream platforms for developing and deploying data warehouse and business intelligence solutions. The vendors that have survived all the market swings over the last 12 months are now emerging with second, third and fourth generation offerings, and the bigger players have now solidified their presence in the appliance space with new offerings.

In my opinion the appliance is becoming a platform for deploying data and applications which are having either a short lifecycle and high complexity  in terms of business value or for deploying applications and data which have a longer lifecycle and lesser complexity in terms if business value.

Vendors such as Aster and Greenplum have propelled the incorporation of Mapreduce to make the platform more developer friendly. Vendors of interest to watch apart from these two and the big five (Netezza, Oracle, HP, Microsoft, IBM) are Infobright, ParAccel and Vertica. The last two are gaining more credibility and adoption, heralding the acceptance of Column Databases as mainstream analytical platforms, for faster analysis of large data volumes.

With so much going around, the Data Warehouse Appliance is certainly not dead and is not all hype. There is definitely substance in the technology and it continues to get better and bigger.

I'm writing this blog from an airplane and connected to the internet. While this is amazing and cool to be connected when being airborne, it also begs a question - Information Governance. We now live in a day and age of twitter and facebook; information sharing has reached new levels and information about anything, anywhere is always happening. Point in case, President Obama's remarks the other day was tweeted immediately and was turned into an instant debate of many dimensions. That information might have helped the people in the context of the conversation, but what about the rest of the world that just read the tweet?

Here is where information governance comes to play - when any information is deemed to be shared one must follow a set of guidelines, these may be as simple as

1. Classifying the content - Personal i.e share with friends and family; Professional - share with co-workers and others in your network; if you have information that is beneficial to others then you can write about it at hundreds of blogs

2. Identifying the context - When you share information on the web, set a context to what you will write about. Without context, any information can be interpreted in many dimensions. Doing this will save you and everyone else time

Public domain data such as twitter can be harmful if sensitive information is shared without rationale. This is one reason many organozations today restrict their webistes from accessing or providing access to social networks. Rather than completely shut access, which is controlled information governance, organizations must setup the office of an information Czar, who will provide guidance for sharable information. Any sensitive material can be restricted from being sent outside the organization.

Information governance is something that we all will learn to manage inour personal and professional  lives as we move into the next realm of information age and embrace social networking as a part of our life.

Analytics has been gaining a lot of attention in the last six plus months. The trend that we are seeing is across all areas products, consumers and services i.e we are seeing more products to address analytical BI, more companies are investing into analytical BI and more service offerings are being built on BI.

Why all this focus on analytics? the one answer that comes to mind is ease of use. But beyond that there are multiple factors enabling the analytical BI space

•  Computing platforms - Computing platforms were a big hinderance to analytics performing, which is a non issue, especially with the advent of data warehouse appliances. The lower cost of the platform and the speed of computing it provides has made the computing and availability of analytical data a non issue.
• Cause and Effect - Executive reporting has changed from plain stock graphs and speedometers to cause and effect analysis. Executives are more interested in Analytical BI, and seek more information than before
• Maturation of vendor offerings - The analytical reporting solutions have evolved over the last year
• Web 2.0 or BI 2.0 - The BI 2.0 effect has begun to change the way we do BI. Real time BI and Right time BI have created a great demand on Analytical BI solutions.
  

As we progress on this timeline, Analytical Solutions are going to become more powerful and easy to use.

The newest solution offfering in this space is from Kalido+Netezza called Kalido KONA Information Appliance. This is an end to end solution from Kalido for BI. Per information from Kalido, "The Kalido KONA Information Appliance addresses the discrete business requirements in specific industries, enabling enterprises to more effectively manage key performance indicators across all areas of business.  It is an end-to-end analytics and reporting solution containing industry-specific business information models and all required hardware and software for data storage, data sourcing and integration, master data management and governance, and analysis and presentation."

More information on this offering is available at www.kalido.com/KONA.

It is clearly a sign of the times. Companies are now seriously looking at Social Analytics as part of their mainstream BI portfolio. Why? why the sudden importance one might wonder. Consider the following situation

Customer A purchases a product from Company XYZ at Store123. They are very happy about the product and the associated service. Chances are this customer will market the product by word of mouth to their immediate contacts. This was the situation till Twitter, MySpace and Facebook became the voice of the customer. Today the same customer almost immediately uses their social network site and blogs about the company, store, product and all the good stuff they experienced. What this does is a very powerful marketing channel for the company and its product, creating a market demand across the globe.

IF the Customer had a negative experience and was very upset, the message from this customer will evoke more similar reactions, and this will end up as a negative branding and marketing for the said company and its product/service.