C-Store Technology

C-Store technology is applied to POS data using analytics and artificial intelligence (AI) to pinpoint specific problems. High performance C-store operators leverage the technology to save time, sell more and reduce theft. POS analytics and AI allow supervisors to pinpoint problems, recognize top performers and coach cashiers on the most important issues.

The pressure of c-store operations demands tools that leverage data to save the time need to follow-up. Hiring, training, meetings and the normal day to day activities consume most of every day. Finding problems quicker is a big help. It just makes sense, experienced managers have fixed almost every possible problem. The solution is not usually the challenge. Rather, the issue is finding or even awareness of the problem. For example, knowing which stores are underselling promotions, seeing too many voids or even learning that cashiers are using their birthdate for every age check.

ETL Performance troubleshooting with Pentaho Data interchange

ETL Performance troubleshooting with Pentaho Data interchange

C-Store Technology
February 17, 2014 — 

System monitoring, memory, partitioning, CPU balancing and disk arrays are all part of making the ETL performance of your Pentaho Data Interchange fast and efficient. System monitoring is a critical first step and catch all for performance issues. As the amount of your data grows, processing the data becomes more of a challenge and can …

Three reasons measuring improves our results

Three reasons measuring improves our results

C-Store Technology
February 15, 2014 — 

C-store operators always ask the best way to save time and make more money. Here are three reasons measuring improves our results: 1. Clarify what is important 2. Understand how we compare 3. Justify financial rewards So you want to know how you measure up. The old saying that you don’t know where you are …

One fast ETL tool - Pentaho PDI

One fast ETL tool – Pentaho PDI

C-Store Technology
February 5, 2014 — 

Extract, transform and loading is a necessary part of many Big Data jobs. We use tools to do it faster and cheaper to move the work to the dashboards and analytics to get results. Read The Full Blog Here

Three results that define 'Big' in Big Data

Three results that define ‘Big’ in Big Data

C-Store Technology
February 5, 2014 — 

Matthew Shoup of LinkedIn provides an insightful way to interpret the ‘Big’ in Big Data. No one cares about the ‘Big’ unless there are results. This approach puts the focus where it matters. Read More From His Post Here

Three results that define 'Big' in Big Data

Defining the ‘Big’ in Big Data

C-Store Technology
January 25, 2014 — 

Redefining ‘Big’ in Big Data – Action, Ideas and Results. Matthew Shoup of LinkedIn provides a wonderful set of ways to interpret the ‘Big’ in Big Data. It is not so much the quantity of data that is important for many companies but rather what is done with it. While having lots of data is …

Never use SQL again for ETL – Pentaho Data Integration reusable flows instead

Never use SQL again for ETL – Pentaho Data Integration reusable flows instead

C-Store Technology
October 7, 2013 — 

Since Pentaho is free and PDI is so easy, our team no longer will use any stand-alone SQL as part of our extract transform and load (ETL) process. Many times we have determined that we only need to extract the data ‘one time’. Inevitably, we need to run it again or something very similar. It …