The data you back up depends on knowing which KPIs are important to understanding your company’s performance. Then include that data in your disaster recovery plan. Credit: Thinkstock As IBM’s general manager of analytics, Rob Thomas’s job is to understand how big data can benefit industries all around the world. In his book The End of Tech Companies, Thomas reported findings from Siemens AG that hold that by 2020, over 50 billion connected devices worldwide will produce 43 zettabytes of digital data. He also discusses how non-IT companies are becoming as well-versed at analytics as their IT peers. With so many connected devices “phoning home” and so much of what we do in our daily lives being tracked by someone somewhere in the ether, it’s no wonder our data centers are bursting at the seams. But do companies need to back up all of that data? Does every last byte of chatter need to become part of our disaster recovery (DR) strategy? As a former database administrator back in the 1990s, I know we constantly kept our DR strategy in the forefront of our minds so that if a new application came online or a user identified a critical new data source, we worked it into our DR strategy right away. Questions we had to answer were, “how critical is this data for our business?” or “how critical is this data for our customers to do business with us?” If either the business or our customers would suffer without it for any duration, it was considered critical business data and put into the first tier of our recovery plan. This logic hasn’t changed: You still back up everything that’s critical to doing business and facilitating customer engagement. But what data do you back up, and how often do you back it up? Your data itself will actually give you the answer. As both IT and non-IT companies dive deeper into understanding their operations through analytics, retaining historical data becomes imperative for companies to be able to plan for the future. But does backing up analytical data mean companies have to rethink their DR strategy? Absolutely. Data becomes a valuable financial asset According to a recent Gartner report titled “2017 CEO Survey: CIOs Must Scale Up Digital Business,” data has become a financial asset as valuable as traditional financial assets. In other words, data is capital. Determining what data to retain and back up can be defined by first knowing which key performance indicators (KPIs) are important to understanding your company’s performance. The secret to knowing which data to retain is knowing your company and what value you and your customers get from each individual piece of data. The better you understand your business’s operations, the easier it will be to pick out information that smoothes those operations and helps your co-workers track processes and progress. The better you understand your customers, the easier it will be to pinpoint data that will help people engage with your company while minimizing turnover. Once you know which KPIs are critical to understanding your bottom line, identifying the data from which those KPIs are derived is the next step. Retaining any other analytic data not related to those KPIs will consume unnecessary resources. Finding the core of which data to retain will help you plan a DR strategy that will enable you to retain and restore critical data. So, to answer the age-old question of to back up or not to back up, your data has the answer. Related content opinion Why banks didn’t ‘rip and replace’ their mainframes In the early 2000’s, companies were ready to ‘rip and replace’ their mainframes for new technology, but what came next was inferior to the processing power of the mainframe. By Jennifer Nelson Sep 17, 2018 3 mins Computers and Peripherals Data Center opinion How mainframes put muscle behind autonomous data maintenance software With the muscle and processing power of the mainframe, autonomous troubleshooting software can handle the drudgery so the DBA can plug into their human ingenuity. By Jennifer Nelson Jun 07, 2018 3 mins System Management Data Center opinion Leverage the power of the mainframe to make sense of your IoT data With ever-increasing IoT data, using ETL to provide real-time analysis won’t cut it. A mainframe, though, can process your data without a hiccup. By Jennifer Nelson Jan 12, 2018 5 mins Internet of Things Computers and Peripherals Data Center Podcasts Videos Resources Events NEWSLETTERS Newsletter Promo Module Test Description for newsletter promo module. Please enter a valid email address Subscribe