We're flying into the future

Canara merges with CPG, combining our AI supported technology with cutting-edge, full-spectrum data center solutions to better design, build and operate the data centers of the future.

Merger Info
About CPG

Remember when data center preventative maintenance was a quarterly, mandatory process that allowed straightforward budgeting and planning?  It was all very orderly, neat and predictable.  Unfortunately, large portions of spending and effort were neither necessary nor productive. However, it can be hard to differentiate the necessary from the excessive without a working crystal ball or a really good rearview mirror.

Using advertising as an example, companies traditionally pitched their products via TV or radio, and metrics were generalized around audience size, frequency and repeat exposures.  Today, marketing analytics have made advertising a much more personal and targeted process.  How many times do you notice the web ad for the hotel or pair of sneakers you just browsed pop up on the search site or in a banner ad?  This is not by accident.  Marketing analytics tools are monitoring behavior and presenting advertising based on data and specific customer behavior.  Technology has fundamentally changed the economics equation of advertising through a data analytics framework.

The Crystal Ball Challenge for Data Centers

Similarly, what we’re experiencing now is technology’s answer to the crystal ball challenge for data centers. Data, analytics and predictive insights are helping firms optimize their approach to maintenance, the same way various web technologies have improved understanding and added predictability and precision to the advertising process. By understanding data center equipment circumstances at a much more detailed level, and leveraging recorded and measured experience, facilities are increasingly able to continue to support uptime objectives, with added insight into the health of their systems while reducing overall cost of maintenance.

This is important for a number of reasons.  Most notably, it supports the ever-present pressure to do more for less – or at least continue to drive costs out of the business and improve operational efficiency.  This is true both from a pure spending perspective as well as from a resource utilization perspective.  Performing condition-driven preventative maintenance saves both time and money.

Use Data to Effectively Manage Preventative Maintenance Programs

The rapid rise of the Internet of Things (IoT) means more and more of the data center infrastructure can be monitored and measured. For facilities that are collecting that data, that means exponentially more information to help drive management decisions and feed facility managers the information necessary to efficiently and effectively manage preventative maintenance programs.  Yet, currently data centers fall short of using the data that’s collected to its fullest capacity.

What those data centers do with that information determines whether they have really improved their situation, or just traded one inefficiency for another.  Figuring out how to integrate the data, and the actionable insights it contains, into operational processes and procedures is the critical final step.