How Data Virtualization Can Prevent Getting Pulled Over by Cops
Ok, forgive the hyperbole in the title since data virtualization doesn’t actually have magic powers to keep you safe from getting ticketed by the police. However, in one specific series of incidents that I recently encountered which did involve getting pulled over by the cops, you’ll see how a little data virtualization could have gone a long way; here’s the story:
Picture the scene: I was running late to the airport for a quick business trip, a scenario I imagine many of you can relate to. As is customary when traveling on tollways around the city of Houston, there was a police cruiser parked on the side of the tollway, presumably looking to catch people speeding. I generally don’t drive much above the speeding limit so I wasn’t overly concerned by their presence, however, I did make sure to doublecheck that I wasn’t over the speed limit. You can imagine my confusion when I saw the police cruiser right on my tail, followed by the all too familiar flashing red and blue lights to let me know I was being pulled over.
“Oh great! Now, I’ll definitely miss my flight!” was my first thought, but I wasn’t too concerned because I assumed it was a misunderstanding. As the officer approached my truck, she informed me that I had $1,600 in toll violations and therefore wasn’t allowed to drive on the tollway.
What? This was news to me!
I told her that this must be some sort of mistake because my online account didn’t have any record of such violations and indicated that my balance was zero. After grudgingly accepting my ticket, and now officially speeding to the airport so as not to miss my flight, I searched my mind in an attempt to figure out how this mistake had occurred.
After doing some research, I figured out that my new license plate was the cause, and it hadn’t been updated in the tollway service provider’s database. You see, I had been driving a new vehicle for about a year and initially registered the temporary plate with the Harris County Toll Road Authority (HCTRA). However, as I replaced that temporary plate with a permanent plate some months later, I forgot that I needed to update the record on the HCTRA website. This meant that every time that I had driven through the EZ tag lane in the 9 months after receiving the new license plate, it was flagged as a toll violation. To add insult to injury, the HCTRA unreasonably charges about $33 per violation, in addition to the $1.50 toll charge and that’s precisely how one can easily rack up $1,600 in toll fees. Naturally, I was livid but at least I understood why.
What does this have to do with data virtualization you say? Hang in there, I’m getting there.
So, after returning from my business trip a few days later, I promptly called the HCTRA on a Friday afternoon to negotiate a lower rate and begrudgingly pay off these charges. We came up with an amount as low as they were willing to go, and although I was angry that I had to pay such a ridiculous sum of money for such an innocent mistake, I was glad this incident was safely behind me, or so I thought. I purposely noted that I made this payment on a Friday afternoon because this is where data virtualization comes in. Are you still with me? Good.
The weekend goes by and on Monday morning I’m driving again on the tollway, passing another police cruiser and this time with no concerns because I’m sure my account is in the clear. But oh no, yet again I see the flashing red and blue lights and I’m pulled over. The cop states again that I have $1,600 of toll violations to which I respond that I had cleared it up and had paid it off already the previous Friday. He goes back to his vehicle, makes some phone calls, then after about 15 minutes comes back to my truck and apologizes for the mistake. Yes, I actually got a cop to apologize for a mistake, but I digress. He told me that since I made the payment on a Friday, the system processes that need to run had not yet run so he was looking at stale data, which didn’t reflect the payment I made.
Are you seeing signs of data virtualization yet?
Yes, me too, but first I’m still in the midst of being angry for getting pulled over again for a mistake. He wrote down his name, badge number, and incident number because he said it is likely that I will get pulled over again because he’s not sure when the system will be updated. Stale data is the bane of everyone’s existence, even people who don’t work with data for a living. So, I thanked him and went on my way hoping to avoid any further interactions with the cops.
The very next day, can you guess what happened to me again, would you believe it? I anticipated what the cop was going to say as he approached my truck so I simply handed him the information that the previous cop had given to me to show that it was a mistake. He went back to his vehicle, verified the information and told me the same old stale data story. He then said that I should probably avoid the tollway for at least a couple more days because I’ll keep getting pulled over until their systems get updated. This is the exact point where the data virtualization bulb switched on in my mind.
I imagine what happened that Friday afternoon when I called the Harris County Toll Road Authority to make payment arrangements was that the customer service person that I dealt with entered that information into an information system of some sort with a status indicating that the payment had been made. After updating that system, I also imagine that there were some batch ETL processes that needed to run in order to update the system that the police use to determine which drivers are in good standing to drive on the toll road. I also imagine that those batch ETL processes don’t run on the weekends, therefore leaving an even a longer time for stale data to lead to erroneous actions like unnecessarily pulling people over who have places to go and people to see.
From the time that I made payment, I would guess it took about 5 calendar days before all systems were updated with the correct information. In my case, this was simply an annoyance. In many other more critical business scenarios, this lag time leading to erroneous business decisions could come at the cost of millions of dollars and in some cases, literal life and death decisions, say in the case of a healthcare provider.
So how would data virtualization have solved this problem?
Simply speaking, data virtualization enables real time access to data that exists in disparate sources. In my case, one of those sources was the system at the Harris County Toll Road Authority containing customer payment information and the other was the system that the Harris Country Police use to determine drivers who are in good standing.
What if the police cruisers were able to view real-time information of a driver’s status, directly from the Toll Road system without having to wait for some batch ETL process to run to update each driver’s status? What if the “check status” button in the police cruiser simply made a web service call to a service hosted in the HCTRA’s data virtualization server which immediately retrieved the real-time status of a driver without having to wait days for ETL to complete?
The answers to these “what ifs” certainly could have saved me about an hour of wasted time that I’ll never get back. Most organizations in today’s data-centric world have similar “what if” questions and the answer to these questions is quite simply, data virtualization.
In today’s fast paced, data-driven, technological landscape where we are accumulating data at historic levels, those who are able to quickly and efficiently access and analyze this data for making critical business decisions, will stand apart from their competitors and win the future. Fast access to data to make informed decisions for all sectors, whether it be banking, retail, insurance, energy, technology, healthcare, government, and yes even police departments, is a critical capability.
Data integration processes can be slow, costly, inefficient, and often involve physically copying data between sources, leading to inefficient operations, delayed responsiveness to critical matters, and data governance complications. Data virtualization enables real time access to data that exists in disparate sources without the need to engage in costly data integration processes.
If I’m lucky, somebody from the Harris County Toll Road Authority or Harris County Police Department, will come across this blog and the data virtualization bulb will be switched on in their mind too. I certainly wouldn’t want to go through this experience again, after all, I’ve got places to go, flights to catch, and data virtualization solutions to sell.
Ask yourself, what similar data integration inefficiencies do you have in your organization and could data virtualization be the magical solution you’ve been looking for?