The role of the traditional librarian is changing quickly and with upgrading their skills to data scientists the librarian can upgrade their skill sets and become one of the hottest employees companies are hiring for.

In Meghalaya region of India there are some interesting characters up for re-election.  Among those running for office include Adolf Lu Hitler and Frankenstein.  

In this 4th article of the 8 part series on ERP data conversion we will be focusing in on the data conversion for ERP around the Quote to Cash processes.  Order to Cash typically includes master data such as customers, sales people, pricing information, and payment terms but may also include configuration rules and configurator Bills of Materials in case of configure-to-order environments in addition to transactional migrations ranging from quotes, sales orders, sales contracts and open invoices through unapplied cash receipts. Additionally revenue/COGS (cost of goods sold) recognition process may also be considered part of the Quote to Cash process.

In my many discussions on Master Data Management (MDM) a common goal is to achieve a single source of truth.  This literally means that data should only be stored once but really in terms of MDM it often really means that the data is consistent and visible in one place.  If you don't have consistency of master data across systems you can end up with differences in the exact same attribute across different systems.  This is bound to happen if the exact same system is maintained in different applications by different people. This does not necessarily mean that the all attributes must be maintained in a single system.  You need to be practical in terms of your approach for best managing the maintenance process.

When deploying ERP, the decision on where/how to manage your master data processes such as customers, suppliers, product master and other key elements are made.  Though the "best practice" recommendation is to have MDM be separated from ERP the decision is not always black and white.  In the following article we break down some key considerations to help decide what is best for your organization.

Data quality has become a political issue with India.  According to OECD Chief Statiistician interview in Economic Times India has a data quality problem and a timeliness problem in their ability to report national statistics such as GDP, social inclusion and sustainability.

Most of us are interested in staying current and working on new things. Here we are talking about Big Data, which is indeed a powerful concept. In this write up, we will share our thoughts on what companies should be doing as the first step to taking advantage of big data.

In this 3rd article of the 8 part series on ERP data conversion we will be focusing in on the data conversion for ERP around the Procure to Pay processes.  

The concept of Big Data has been hyped up particularly in 2012 and as you can see from Google Search trends on "Big Data" below has increased 5X in the last 12 months.  With the amount of data being generated executives and business managers are drooling over what kind of insight can be found from the massive amounts of data that companies are generating currently.  The ability to execute on this insight is still a challenge.

In this second part of the 8 part series on ERP data conversion we will be focusing in on the data migration for ERP around Record to Report or Financial applications.  The complexity of these conversions really depend on the level of change as well as the decision on amount of history to load in to the new ERP system.