How to use Data Analytics in Customer Service Solutions

September 19, 2015
  1. Collect data for the entire customer journey
  2. Apply analytics to better understand your customers and personalize the journey
  3. Use predictive analytics and machine learning to anticipate important events
  4. Continuously tune the analytics platform using feedback

SolrCloud Terminology

October 17, 2014

Excellent article and diagram giving a high level overview of SolrCloud terminology –

Data Ingestion for Enterprise Data Platforms

May 5, 2014

The Ingestion Box in the reference architecture is displayed as the smallest box.  However, this is the component that integrates with all the available data sources.  This tends to be among the most complex and time consuming task, but tends to be relegated to a lower priority which is a big mistake.

One needs to prioritize the data sources that generate maximum value and ensure we can ingest the data into the Big Data platform for subsequent “cool” analytics.

In my experience, it is also extremely important to have a robust User Interface for the ingestion section.  Otherwise, there could be a series of manual steps leading to errors and ingestion of “bad” data that will minimize impact of subsequent analytics.



Apache SOLR or Amazon CloudSearch

May 4, 2014

Very well written article comparing the two search technologies –

The two Real Enterprise Content Management Software Trends for 2014

April 22, 2014

1 –  Modern, Minimalistic, Intuitive User Interfaces

Customers have become accustomed to a Dropbox like user interface.  Enterprise systems need to catch up and build software that is intuitive and easy to use across all devices


2 – Value for Business

We need to imagine ECM software beyond managing data and minimizing risk. This should be inherent in the software.  We need to automate workflows.  Automating workflows includes eliminating unnecessary steps.  E.g. if there is no value in a person approving a document, we should not blindly automate this step simply because it is part of the current workflow.  We need to critically evaluate each step and think how to provide true value for expected objective.




Profitless Startups

April 12, 2014

Interesting article –

These startups do provide hope for aspiring entrepreneurs, challenges for the founders and employees and propels the innovation engine.  Don’t tax payers benefit when there is an uptick in innovation?


Minimum Viable Product for Enterprise Customers

March 2, 2014

You need to iterate fast to release, but not with a  poor quality product that does not address at least basic needs in an Enterprise situation

Firstly, it takes longer to identify test customers in a corporate setting vs a consumer website and enterprise customers have a higher expectation of software.  More importantly, your channel can make or break your product and with limited testing resources you don’t want to jeopardize the opportunity.

The right balance needs to be identified, with the right minimal features built well and working solidly.

Improving IT ops efficiency is a business need

December 14, 2013

As Facebook has demonstrated, there is business value to improving efficiency of IT ops. Large organizations tend to relegate internal operational efficie to a lower priority and need to open their eyes to opportunities that open up when internal efficiencies are accomplished.

Check out Facebook IT ops

Is Truecrypt Secure?

December 6, 2013

NSA feels it has an obligation to undermine major tools protecting our privacy – check out  NSA has apparently tried to get to truecrypt but without much success. They have now formalized a project to formally audit (read break into it) truecrypt –

Should we accept eventual consistency?

November 3, 2013

The NoSQL solutions available today provide distributed architectures with fault tolerance and scalability. However, to provide these benefits many NoSQL solutions have given up the strong data consistency and isolation guarantees provided by relational databases, coining a new term – “eventually consistent” – to describe their weak data consistency guarantees.

Is this acceptable? Shouldn’t we be demanding at least close to real time consistency?

A must read article by Dave Rosenthal