The hardest part of any data analysis project is ensuring the source is providing accurate data formatted correctly.

It does no good to run an automated report out of a front-end system and then copy-paste into a spreadsheet so you could then analyze. There are scripts and other methods that could be utilized to eliminate all the most tedious aspects of cleaning the data set. That saves time and creates efficiencies, which translates to a better ROI where it matters most.

What is a warehouse? A warehouse is a centralized repository of all the sources of data that come into a company. It creates efficiencies for analysis and dashboarding as well as makes possible the creation of new fields via calculations across data sources. So if we pull in something from sales and something from another department we can write custom calculations — the number of calls a rep does and another system has the number of closes, we can then create a calculation to show calls to close ratio. Also provides a single version of the truth — a single place for all reporting to come from without conflicting conclusions. Finally, maintenance and admin can be centralized and monitored to ensure more up time.

Creating a connection to the data source: This could be an API or SQL connection to transport the data at an automated timeframe. A common fallacy is you need to pull all the data into the same place — That’s not a good idea. Instead, we can help you pick the most important data sets and set the data retention rules. Doing so keeps your warehouse cleaner and more efficient and cuts down on storage costs.

Cleaning the data: This is typically the most tedious of tasks — spelling out East or using “E” on an address? Abbreviations, extra commas or spaces, converting dates to read as dates and not text, etc. Customized scripts clean the data for you.

Writing to the database: This is where automated routines are set and pulled into a usable format. This is a controlled, centralized place with multiple data sets that make analysis and customized calculations easy.

Now the data is ready for use. See (Dashboarding, etc.) for more information.