Data Management

Data Management
Data Centers in 2021Data Centers in 2021

Have your data center priorities changed? Benchmark where you’re at with data centers against your peers.

Is moving data storage from on-prem to public cloud always cost effective?

Top Answer: Only if appropriately designed and the right storage is used for the right data type. Likely you don't need all your data all the time, so it's important to put archival data on a different storage type than daily accessed data. Aside from how often you access the data, it's important how many transactions on the data you perform. If you are copying/moving the data periodically, it's important to have it within the same region for the egress cost. I've put terabytes of data into a storage account in the cloud and have chosen the cheaper type per GB, only to find that thousands of transactions are done on that data daily. The total monthly cost of all the transactions far exceeded the price per GB, so by switching it to a storage account that is more expensive per GB but cheaper per transaction, the overall cost significantly decreased. For example, recently, I have reduced our data cost for backups by 85% by moving it from one object storage vendor to another. It's all about what makes sense for what type of data. Don't restrict yourself to using one type of storage or one vendor; explore and do the math on what makes sense for your situation.

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How do you approach data quality issues within your ITSM framework?

Top Answer: First of all you must assume that ITSM is not perfect. Not even the data. On the other way you will need efficient and well qualified resources.  Data is always tough to correct but is doable

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Enterprise data architects: What are the top KPIs to measure a successful enterprise architecture program by?

Top Answer: My approach starts at the project level - I determine what projects are being greenlit within the program and why. Each project should have its own KPI that contributes to the evaluation of project-level success and these KPI should be defined to represent the goals of the project stakeholders.  Assuming each project has disparate goals focused on localized business value, I layer the meta-KPI on top of the project KPI and I measure the success rate of the whole program by looking at  1) the success rate of delivery on project level KPI 2) the time to value  3) change failure rate 4) and because my experience tells me that enterprise architect programs are notoriously divisive and disenfranchising to production developers I generally have a "comms and inclusion" mandate baked into the operating methodology of the team that I will also measure to determine if the team is bringing others along with the vision. Assuming the enterprise architecture program has its own goals - my current implementation of this function does - it gets much easier. The KPI are defined directly against those goals with the addition of my "comms and inclusion" KPI. 

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What is the difference between data governance vs data management?

Top Answer: The difference between the 2 is that data governance establishes/sets the policies and procedures around the data, while data management enacts those policies and procedures to compile and use that data for any decision-making

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Adopting Data-as-a-ServiceAdopting Data-as-a-Service

What does "data-as-a-service" mean? 100 IT execs share their thoughts with the Pulse community.

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What are the biggest challenges that Chief Data Officers (CDOs) face?

Top Answer: A lot of it has to do with keeping up with current regulations around the world. The most challenging aspect of being a CDO is that you act as the conduit from various regulatory bodies to the IT organization. A lot of IT organizations have different perspectives on how to interpret those laws and in many cases, there's no upside for someone to not be conservative. If I'm in risk and compliance, or InfoSec, it looks bad on me if data is breached or lost because someone had access to it. So there's little incentive to be able to allow free access to data even though it could mean helping the business do things. As the conduit between these groups, being a CDO is about helping the business find a balance by measuring the level of risk to make informed decisions with appropriate levels of materiality. In some cases it’s not just about saying “no,” it's getting people to all align on what is permissible, and what the right balance of risk is for us to operate as an organization.

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How do you approach managing and protecting customer data?

Top Answer: There are a lot of things that you need to take into account. The first thing is that customer data falls into two buckets. One bucket is what we know about you as a customer or person; the second bucket is behavioral data. The combination of those two buckets is powerful — it allows you to create customized solutions, offerings and experiences for customers. But on the other hand, it’s also a deep, rich picture of a person and if that data is exposed to people who would use it for nefarious purposes, that can have very serious consequences. You need to understand what data you have about a customer. The data that is captured by an organization traverses the full lifecycle of the relationship that a company has with a customer. It can start with prospecting: I can go out and buy a list of people that contains their data. I can then go to a data amalgamator that is collecting other pieces of information about people, and I can then enrich that list in view of that customer, with data that I've purchased. So they haven't even been a customer yet, and I've already got a lot of information about them. Then when I've marketed them so that they visit the site or come into a branch to apply for a product or a service, they fill out an application. In financial services and healthcare, you're providing a huge amount of information to a company when you fill out an application, which is an intimate view of you as a person.  The behavioral data is gathered when you traverse a website. Companies are taking pictures of what sites you came from, what sites you visit when you leave theirs, what you're doing or looking at while you're on those sites, etc. Even when you call into a call center, there are different things that you might do when you call in and a lot of data is collected on the phone; apart from the transactional components, you can get voice prints of people from those conversations. So from what you're buying, to your payment patterns, to what you do with the products that you have, a company’s systems capture all of that. Considering the lifecycle of all of that data, as an organization, you need to know what data you have and in which systems that data is located. Then you need to determine what you have to protect, according to applicable laws and regulations around privacy and affiliate sharing.

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If you are a current SAP customer, when do you plan to migrate to SAP S/4HANA?

Top Answer: No plan to migrate soon.

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