Streamlined Data Integration

"Best Practices"

Raw data, as it comes from its original source, is often unsuitable for analysis and reporting. In many cases it is "dirty", containing incorrect or invalid information due to human input error or machine malfunctions. In other cases it is too voluminous to process using conventional technologies. Standard practice is therefore to clean and summarize the data as it is loaded into the database, so that all reporting starts with the transformed data. This is the familiar data integration approach using an ETL (extract, transform and load) process.

Challenges

There are significant problems with the standard approach.

1. Almost all transformations result in information loss. In the case of summarization this is patently obvious, but it is true even when data is cleansed.
2. It takes a long time to figure out how to clean all the data and summarize it, and then to develop the ETL processes. The database cannot be built and delivered until all that work is done.

1010data's Way

1010data customers are able to take a different path. Our platform is powerful enough to support the analysis of raw data at its most granular level, and fast enough to allow analysts to cleanse the data on the fly. This gives users much faster access to data and an unmatched ability to analyze it in new ways.