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Running a business without some cloud support is rare these days. Yet, when crafting a cloud strategy, companies seem to make some common mistakes. There are several of them here.

Making Your Cloud Strategy Only IT Strategy

Gartner said this week at its IT Infrastructure, Operations and Cloud Strategies conference that a successful cloud strategy requires support from IT outsiders.

“Business and IT leaders should avoid the mistake of building an IT-focused strategy and then trying to ‘sell’ it to the rest of the business,” Marco Minardi, vice president analyst at Gartner, said in a statement. “Business and IT must be equal partners in the definition of cloud strategy.”

“Technology for technology’s sake is generally not a good idea,” said David Smith, vice president analyst at Gartner.

“Anytime you do something, you want a clear vision of why you’re doing it, what the business reason is,” Smith told TechNewsWorld.

“People look at it and say, ‘It’s technology. Let the technologists deal with it,'” he continued. “What happens then is that people focus on the adoption phase – which is about how you do things and when – which is different from the strategy part, which focuses on whether you What are you doing and why are you doing it.”

Change in exit strategy

Organizations often do not have an exit strategy in place with a cloud provider because they do not envision leaving the cloud. Furthermore, formulating such a strategy can be difficult. “People don’t like the answers they’re going to get, so they avoid it,” Smith said.

During the early days of the cloud, vendor lock-in was a significant fear, but that’s less the case today, said Tracy Wu, an analyst at Forrester, a national market research company headquartered in Cambridge, Mass.

“Some companies will prefer to be locked down with a specific vendor to get to market sooner or take advantage of specific pricing or services,” Wu told TechNewsWorld.

Still, she said, “organizations should always think of a plan B whether it’s the cloud or some other option.”

“That being said,” he continued, “it’s rare to hear of companies that actually pull out of a specific cloud provider completely.”

Confusing cloud strategy planning with cloud implementation planning

Organizations should always have a cloud strategy plan before implementation or adoption. Strategic planning is created during a decision phase in which business and IT leaders determine the role of cloud computing in the organization. Next comes a cloud implementation plan, which puts the cloud strategy into effect.

“If you call something a strategy, and it’s really an adoption plan, you end up with hundreds of pages of details that aren’t of interest to business people, so you scare them away, Smith explained.

“A good cloud strategy should be a short and consumable document, consisting of 10 to 20 pages or slides,” Meinardi said.

Some areas commonly overlooked in cloud strategy planning, as identified by Wu, include key goals, targeted revenue targets, new revenue streams, and the new business or traction the organization wants to build using the cloud.

“Too often, companies get into a rush to adopt the cloud and only think about the implementation aspect without thinking of the higher goals or the larger strategy at hand,” he said.

Comparing a Cloud Strategy to Migrating Everything to the Cloud

Minardi explained that many business and IT leaders shy away from formulating a cloud strategy because it would mean they would be forced to use cloud computing for everything. “Organizations should keep an open mind and partner with a non-cloud technology expert, such as an enterprise architect, who can bring a comprehensive perspective to the definition of your cloud strategy,” he advised.

On the other hand, some organizations believe that moving to the cloud is an easy task.

“One of the biggest challenges companies face is they think they can take what’s going on and move it to the cloud,” said Jack E. Gold, founder and principal analyst at J.Gold Associates ” IT Consulting Company Northborough, Mass.

“To get the best benefits from a cloud implementation, you need to rethink your applications, solutions, architecture and strategy,” Gold told TechNewsWorld.

“They also don’t do a great job of deciding which apps should stay on-premises and which should move to cloud environments,” he added.

“There are a lot of apps that will never go to the cloud,” he continued. “They’ve been around for 10 years. They’re going to be around for another 10 years. Why bother?”

Outsourcing Evolution of Your Cloud Strategy

As tempting as it may be for other business and IT leaders to build a cloud strategy, Gartner doesn’t recommend it. Outsourcing is very important, it said.

“It makes sense to outsource during the adoption phase where you may need outside expertise,” Smith said. “What happens, though, is that it’s all too easy to put yourself in a position where you’re allowing your vendors to define your strategy.”

“If you want to go out and get help from someone who knows what they’re doing, that’s fine, but you have to look at what they’re doing,” Gold said. “You don’t want to just throw checks at the wall. You need to be involved in figuring out your strategy, even if someone else is helping you put it together.

Wu agreed. “I wouldn’t say that outsourcing strategy is a bad idea unless the entire strategy is being outsourced, with absolutely no direction from the company,” she said. “It’s really a big part of what leading global systems integrators do when they help design and implement cloud strategy.”

Comparing cloud strategy to ‘cloud first’

Gartner explained that the “cloud first” approach means that when someone wants to create or own new assets, the public cloud is the default place to do so.

“But cloud-first doesn’t mean cloud only,” Mainardi said. “If businesses and IT leaders adopt a cloud-first principle, their strategy must work on exceptions to the default option that will apply elsewhere besides the cloud.”

Wu notes that some of the assets best placed outside of the cloud are data with heavy residency requirements (data cannot leave a specific region or country), data that needs to be physically located outside of the location being processed for latency or performance reasons. Must be relatively close, and where data exits is very expensive, such as in big data applications and AI.

Believes it’s not too late to design a cloud strategy

Gartner argues that it is never too late to develop a cloud strategy. “If organizations drive cloud adoption without a strategy in place, it will ultimately lead to resistance from those who are not aligned on the key drivers and principles of the strategy,” Meinardi said. “As a result, this resistance will slow cloud adoption and potentially jeopardize the entire cloud project.”

Do you know whether your company data is clean and well managed? Why does it matter anyway?

Without a working governance plan, you may have no company to worry about – data-wise.

Data governance is a collection of practices and procedures establishing rules, policies and procedures that ensure data accuracy, quality, reliability and security. It ensures the formal management of data assets within an organization.

Everyone in business understands the need to have and use clean data. But making sure it’s clean and usable is a bigger challenge, according to David Kolinek, vice president of product management at Atacama.

This challenge is compounded when business users have to rely on scarce technical resources. Often, no one person oversees data governance, or that person doesn’t have a complete understanding of how the data will be used and how to clean it up.

This is where Atacama comes into play. The company’s mission is to provide a solution that even people without technical knowledge, such as SQL skills, can use to find the data they need, evaluate its quality, understand any issues How to fix that and determine if that data will serve their purposes.

“With Atacama, business users don’t need to involve IT to manage, access and clean their data,” Kolinek told TechNewsWorld.

Keeping in mind the users

Atacama was founded in 2007 and was originally bootstrapped.

It started as a part of a consulting company, Edstra, which is still in business today. However, Atacama focused on software rather than consulting. So management spun off that operation as a product company that addresses data quality issues.

Atacama started with a basic approach – an engine that did basic data cleaning and transformation. But it still requires an expert user because of the user-supplied configuration.

“So, we added a visual presentation for the steps enabling things like data transformation and cleanup. This made it a low-code platform because users were able to do most of the work using just the application user interface. But that’s right now.” was also a fat-client platform,” Kolinek explained.

However, the current version is designed with the non-technical user in mind. The software includes a thin client, a focus on automation, and an easy-to-use interface.

“But what really stands out is the user experience, made up of the seamless integration that we were able to achieve with the 13th version of our engine. It delivers robust performance that is crafted to perfection,” he said. offered.

Digging deeper into data management issues

I asked Kolinek to discuss the issues of data governance and quality further. Here is our conversation.

TechNewsWorld: How is Atacama’s concept of centralizing or consolidating data management different from other cloud systems such as Microsoft, Salesforce, AWS and Google Cloud?

David Kolinek: We are platform agnostic and do not target a specific technology. Microsoft and AWS have their own native solutions that work well, but only within their own infrastructure. Our portfolio is wide open so it can serve all use cases that should be included in any infrastructure.

In addition, we have data processing capabilities that not all cloud providers have. Metadata is useful for automated processing, generating more metadata, which can be used for additional analysis.

We have developed both these technologies in-house so that we can provide native integration. As a result, we can provide a better user experience and complete automation.

How is this concept different from the notion of standardization of data?

David Kolinek
David Kolinek
Vice President of Product Management,
atacama

Kolinek: Standardization is just one of many things we do. Typically, standardization can be easily automated, in the same way that we can automate cleaning or data enrichment. We also provide manual data correction when resolving certain issues, such as missing Social Security numbers.

We cannot generate SSN but we can get date of birth from other information. So, standardization is no different. It is a subset of things that improve quality. But for us it is not just about data standardization. It is about having good quality data so that the information can be leveraged properly.

How does Atacama’s data management platform benefit users?

Kolinek: User experience is really our biggest advantage, and the platform is ideal for handling multiple individuals. Companies need to enable both business users and IT people when it comes to data management. This requires a solution for business and IT to collaborate.

Another great advantage of our platform is the strong synergy between data processing and metadata management that it provides.

Most other data management vendors cover only one of these areas. We also use machine learning and a rules-based approach and validation/standardization, both of which, again, are not supported by other vendors.

Furthermore, because we are ignorant of technology, users can connect to many different technologies from a single platform. With edge processing, for example, you can configure something in the Atacama One once, and the platform will translate it for different platforms.

Does Atacama’s platform lock-in users the same way proprietary software often does?

Kolinek: We have developed all the main components of the platform ourselves. They are tightly integrated together. There has been a huge wave of acquisitions in this space lately, with big sellers buying out smaller sellers to fill in the gaps. In some cases, you are actually buying and managing not one platform, but several.

With Atacama, you can buy just one module, such as Data Quality/Standardization, and later expand to others, such as Master Data Management (MDM). It all works together seamlessly. Just activate our modules as you need them. This makes it easy for customers to start small and expand when the time is right.

Why is the Integrated Data Platform so important in this process?

Kolinek: The biggest advantage of a unified platform is that companies are not looking for a point-to-point solution to a single problem like data standardization. It is all interconnected.

For example, to standardize you must verify the quality of the data, and for that, you must first find and catalog it. If you have an issue, even though it may seem like a discrete problem, it probably involves many other aspects of data management.

The beauty of an integrated platform is that in most use cases, you have a solution with native integration, and you can start using other modules.

What role do AI and ML play today in data governance, data quality and master data management? How is this changing the process?

Kolinek: Machine learning enables customers to be more proactive. First, you’ll identify and report a problem. One has to check what went wrong and see if there is anything wrong with the data. You would then create a rule for data quality to prevent repetition. It’s all reactive and based on something being broken down, found, reported and fixed again.

Again, ML lets you be proactive. You give it training data instead of rules. The platform then detects differences in patterns and identifies discrepancies to help you realize there was a problem. This is not possible with a rule-based approach, and is very easy to measure if you have a large amount of data sources. The more data you have, the better the training and its accuracy.

Aside from cost savings, what benefits can enterprises gain from consolidating their data repositories? For example, does it improve security, CX results, etc.?

Kolinek: This improves safety and minimizes potential future leaks. For example, we had customers who were storing data that no one was using. In many cases, they didn’t even know the data existed! Now, they are not only integrating their technology stack, but they can also see all the stored data.

It is also very easy to add newcomers to the platform with consolidated data. The more transparent the environment, the sooner people will be able to use it and start getting value.

It is not so much about saving money as it is about leveraging all your data to generate a competitive advantage and generate additional revenue. It provides data scientists with the means to build things that will drive business forward.

What are the steps in adopting a data management platform?

Kolinek: Start with a preliminary analysis. Focus on the biggest issues the company wants to tackle and select platform modules to address them. It is important to define goals at this stage. Which KPIs do you want to target? What level of ID do you want to achieve? These are questions you should ask.

Next, you need a champion to drive execution and identify the key stakeholders driving the initiative. This requires extensive communication between various stakeholders, so it is important that one focuses on educating others about the benefits and helping the teams on the system. Then comes the implementation phase where you address the key issues identified in the analysis, followed by the rollout.

Finally, think about the next set of issues that need to be addressed, and if necessary, enable additional modules in the platform to achieve those goals. The worst part is buying a device and providing it, but not providing any service, education or support. This will ensure that the adoption rate will be low. Education, support and service are very important for the adoption phase.