How to Create a Data-Driven Culture

data-driven-1500x630 How to Create a Data-Driven Culture

We are truly in the digital age; data in every enterprise is growing at an exponential rate. A report from Forrester shows that businesses with a data-driven culture are growing 30% annually. And with this growth, our statistical analyses are becoming more accurate too. But one thing to remember is that as humans, when we see success we tend to stick to the behaviours we practiced before the success happened. As a result, sometimes it’s easy to get stuck in one mode of doing things. As well, we often fall into the trap of having data silos confined to only a certain team or project. But why? Why not make data accessible all through the entire organization and allow business leaders to make faster, better-informed decisions. And here’s where creating a data-driven culture comes in.

What is a Data-Driven Culture?

Although it’s a term that’s being used frequently in the technology community nowadays, what does it really entail? Essentially, having a data-driven culture means treating your data as the main resource and educator for every facet of the organization. Using data and analyses allows team members to make better-informed decisions that aren’t as skewed by what “feels right”. Although emotion is important, a part of what makes us human, it’s easy to be swayed into a less than optimal situation. There are a few main components that are crucial to securing a data-driven culture. Firstly, every team member needs access to high-quality data. But not only that, they need the tools and background knowledge to know how to implement the data itself. Having a tool like a central database is incredibly powerful, but only when the people using it know how to get the most out of it. 

Why is it Important?

For most businesses, the customer or client is the priority all the way through the business model. Companies with a data-driven culture better satisfy customers. With fact-based innovation, decision making becomes efficient. Strategies are clarified and backed by hard data. Having data scientists available to all branches of a company actually simplifies concepts, as counterintuitive as that might sound. More people leading to less entropy? With a data-driven culture, that’s the reality. Understanding and implementing these techniques offer the upper hand to the company, especially when combined with team training. 

Ways to Create a Data-Driven Culture

  • Change the Culture

At the root of it all, a change into a data-driven culture is a change in mindset on all levels. And the only way to incentivize this shift is to identify and communicate the necessity and importance of data. Make sure your team understands why data is such a vital part of an organization, and how it will help not only their own work, but the organization as a whole.

  • Lead With a Top-Down Approach 

Leading by example has always been a word from the wise. A top-down approach sets clear goals and expectations for all members of the organization, C-suite or otherwise. When the top executives show that they are investing time, energy, and mind space into a new process, others will follow suit. This will help change the aforementioned mindset.

  • Invest in High-Quality Data Infrastructure

Just like with anything else, when you are starting out, it’s usually beneficial to have durable, reliable resources. The same goes for a data-driven culture. Making sure to invest in high-quality data infrastructure demonstrates the emphasis that the leadership is putting into being data-centred. As well as this, it assures fewer bumps down the road due to technical instability. 

  • Establish Accessibility

The whole idea behind having data as one’s main resource is that the whole company gets to benefit from the statistics. It’s crucial to make sure that every team member can access information, whether it’s across divisions or not. Creating those inter-team relationships and communication between projects not only fosters community, but also a wider awareness of what else is going on. Additionally, when everyone is working from the same dataset, it’s less likely that analyses from different sectors won’t be in alignment.

  • Keep An Open Mind

Arguably the most pivotal part of adapting to a new practice is keeping an open mind. It can be difficult sometimes. Understand that data may be surprising and contrary to your belief, but it’s up to how your organization chooses to accept and reflect on it. Getting in the habit of backing all decisions with analytics and data points, increases credibility and provides fact-based evidence for decisions; this is great for communicating with clients as well. 

Optimus Information can help create a strategy and roadmap for your Data & AI initiatives and use your data for actionable intelligence to maximize the business impact.


Contact us if you want to learn more.


How to Overcome Data Migration Hurdles

data-center How to Overcome Data Migration Hurdles

Overcome Data Migration Hurdles

We overcome data migration hurdles when we plan around them. Recently, we migrated a client’s 20 terabyte SQL server on an on-prem database running an old operating system. We loved the challenge of the task and each problem we solved. We learned a few lessons along the way, and we’d like to share them with you. This article examines possible hurdles you might face when migrating an overextended SQL server with legacy schema to Azure, and which data migration method might serve your organization’s needs.

Azure Site Recovery

Azure provides a number of technologies around site recovery. Those technologies can also be used to trick your system into a behind-the-scenes migration to the cloud. Typically, this Azure Site Recovery is used to create a backup in case of a failover. However, you can set up an existing on-prem datacenter to backup to the Azure datacenter. So, not only is the data backed-up, but it’s now on the cloud (and ready to make use of other Azure services). Beware though: some data centers are running on older operating systems that won’t support Azure Site Recovery.

Physical Migration with Data Box

Physical migration is like using a giant USB stick called a data box. In this scenario, the data box is physically hooked up to the data center, and all the SQL data files are transferred. The device is then taken to a Microsoft server facility where it is hooked up, and all the data is downloaded to several storage accounts. Keep in mind: the data center and Microsoft server facility would need to be relatively close in proximity to one another and you will need to migrate any new data accumulated from your backup point.  


Replication is another method that can be used for data migration. Replication copies and distributes data and database objects from one database to another. It then synchronizes between databases to maintain consistency. However, this method can take a long period of time because it is restricted by the bandwidth available. Relying on a relatively slow bandwidth to migrate 20 terabytes of data could take a month for the system to sync up. 

Replication can be use to migrate any data that may have accumulated while transporting the data box. Since the data box would have all the data up to a specific backup point, replication could be used to synchronize, and therefore, migrate the remaining data. However, when replication is used, the data schema in your product needs to be conducive to replication. That means, tables need to use a primary key, which uniquely identifies each row/record in a database table, and Azure backups need to be stored in standard SQL backup format. Even with these things in place, using replication still might not be an option if there is legacy technical debt in your schema. 

Azure ExpressRoute

Azure ExpressRoute lets you connect your on-prem networks to Azure over a private connection. Since the connections don’t go over the public Internet, this offers more reliability, faster speeds, consistent latencies, and higher security. Another data migration hurdle is having a lot of data to migrate and a small window to do it in (e.g. 48 hours over the weekend). Having a faster network speed is crucial in this scenario. Watch out for bottlenecks! Read on to plan ahead.

To avoid a bottleneck, you will need to find a balance between your network, VM, and disk speeds. Here are a few things you’ll want to consider:

  • Is your VM storage optimized? Storage optimized VM sizes offer high disk throughput and input-output speeds. This is ideal for Big Data, SQL, NoSQL databases, data warehousing, and large transactional databases.
  • Is your VM memory optimized? Memory optimized VM sizes offer a high memory-to-CPU ratio.
  • Do you have the right disk size? The wrong disk size can limit your speed because it won’t have the throughput needed.
  • Are you copying from on-prem disks to storage accounts on Azure or to managed disks? If so, you’ll need to use a copy tool like AZCopy. However, depending on what you’re copying from and to, there might not be a commercially available tool.

Overcoming data migration hurdles can quickly get quite complex. Leveraging the help of Azure experts can save you time and keep you on budget. Contact us to schedule a complimentary discovery session with one of our solution architects.