The value of data increases as the time to use it consistently decreases. What does that mean? Technologies capable of moving data across domains fast are gaining favor in the market. This blog post, sponsored by WANdisco, will explore the relationship among data value, data consistency and time.
Do you remember playing “telephone,” the game where a statement is whispered sequentially through a chain of people to see how it changes? Annie might start with “Technologies that move data are really important,” but Joe, after the statement hops 15 people, might end with, “Harpies are mythical creatures that terrorize technologists.”
It’s a fun game that often baffles kids who just can’t believe that a message would transform in flight like that. But it stops being fun when the message is operational. Thus, “Look out for the harpie, Joe” transforming into “Books are quaint in the digital age” doesn’t help Joe as he’s spirited away by a bird with a human face.
That’s the problem that IT organizations increasingly face as digital businesses try to extract greater value from their data assets. And it has the potential to dramatically undermine the opportunities of digital business: Businesses must have high-quality capabilities to move data at the right price, with the right security and according to crucial business needs.
Let me explain. First, a “digital business” is different from “a business” in one simple way: A digital business uses data to differentially create and sustain customers. In other words, a digital business seeks to maximize returns on data assets.
Second, data assets are different from other kinds of assets in that data can be copy, shared, transformed and integrated with relative ease. It has, as an economist might say, a “low asset specificity”: A data asset can be applied to a lot of different uses, whereas most assets feature attributes that serve particular, specialized purposes.
Third, that means that the value of data assets increases as they are shared in a consistent and timely way.
CIOs who seek to drive returns on data assets suffer the consequences of the telephone game all the time. Most technologies for sharing data over any distance introduce either consistency or latency problems into the systems they support. Sometimes, that’s OK, such as when you’re moving bulk data within a data warehouse.
Other times, though, it’s not. For example, moving operational data from a “hot” site to a backup site would be best served by a technology that ensures data consistency without introducing significant synchronization problems between the two sites. Historically, to do that we used either batch tools, which introduced latency issues, or replication tools, which relaxed consistency rules.
As the digital business demands for data consistency increase, tools that can negate the “telephone game” problem at scale become even more important.