Data Modelling and ETL

etl

Data modelling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Data modelling is the first step in understanding the requirement & converting thoughts into work. Data modelling is routinely used in conjunction with a database management system. Data that has been modelled and made ready for this system can be identified in various ways, such as according to what they represent or how they relate to other data. The idea is to make data as presentable as possible, so analysis and integration can be done with as little effort as necessary.

We can help you in creation of the best data models for you, by first understanding your requirements, selecting which data modelling technique would best suit your requirements & hence provide you a data model which helps you in your BI requirements as well as.

ETL is a key process to build Data Warehouse & at helical, we use Talend and Pentaho Data Integrator to manage, integrate and migrate your enterprise data efficiently.

ETL can be considerably complex. Also, in operational systems the amount of data can be to the tunes of terabytes. Increasing volumes of data often requires designs that scale from real-time change data capture for continuous transformation & update. ETL can however be an expensive process: not only because it requires a lot of hardware and software resource, but also well known proprietary ETL-tools do not come cheap. Open Source ETL-tools are more cheaper alternative to proprietary tools without compromising on any functionality part. We empower the end user with support, documentation & relevant training as well.

Major advantage that we have working with open source ETL tools is that we have the ability to access and extend source code to best suit your needs. We provide customized solution which suits your business requirement perfectly.

The extraction, transformation and loading (ETL) of data is the key to success in a BI system that lets you manage the quality of the data properly.

We ensure the cleanliness and quality of their data by using powerful ETL and Data Quality solutions.
Experts in integrating all sources of data, transactional, unstructured, external creating consistent patterns in the organization.

Centralization of procedures, so as to ensure coherence and consistency of the exchanged data from different sources.
Avoid redundancy of calculations: if there is data previously calculated in the operational databases should not be re-calculated in the extraction. This premise seeks to achieve two objectives:

  • Improve process performance
  • Avoid possible inconsistencies between the results of operational systems and those obtained in the DW.

Establishing points of “quality control” and validation:

  • Technical: ensuring the correct execution of processes
  • Functional: reports generically to validate the data entered.

Implement processes charging information, possible errors in the initial information.
Consider the possibility of intermediate tables using the atomic level of information to be treated.