Table of Contents
- What is Data Architecture
- A Shift from Ancient to Modern
- What are the benefits?
- Steps to designing a data architecture
- Data architecture in the cloud
- Designing a data architecture for the cloud
- Security and privacy implications of data architectures in the cloud
- Advantages of data architecture in the cloud
- The future of data architectures in the cloud
What is Data Architecture?
In the last couple of years, firms have relied on data and information to create new business models. Back in the day, Data Architecture was a technical decision. Times have since changed. Data Architecture now creates a middle ground between technical execution and business strategy.
Data Management Body of Knowledge (DMBOK) describes Data Architecture as "Data strategy specifications that outline the current state, describe data requirements, direct data integration and manage data assets."
The strategy of any organization relies on effective use of data. Data Architecture provides a set of policies for a solid foundation in any business model. Data Architecture has guidelines for many processes. These processes include data collection, usage, processing, storage, and integration with different systems.
The individual components of Data Architecture include the outcomes, activities, and behaviors. These components cover the artifacts, means of implementing the architecture's intentions, and the different interactions.
In this data architecture guide, we will go through all the components of data architecture. We'll also see how these solutions can make life easier for your data team.
A Shift from Ancient to Modern
Data architects align the data environment of an organization with their strategies. Keeping in line with the tenets of good architecture, architects work from the consumers to data sources. These practices customize the architect to the specific requirements of the organization.
Static data warehouses were the order of the day in years past. These warehouses hardly responded to the constant changes in the business environment. Organizations ended up with a raw deal. The frustrations from minimal ROI led to new data solutions that adapt to changes in the market. Organizations have also used data lakes to store raw data. Though the data lakes require large storage capacities, firms can analyze the data for any purpose. Lack of efficient data governance strategies has, however, plagued this resource.
While the present-day data architecture will still have a data warehouse, there's more to it. The warehouse is part of a data environment that is both flexible and agile. Each individual receives tailored access from the adaptable architecture.
Building a Modern Data Architecture – Things to keep in mind
Here are a couple of factors to consider when building a modernized architecture.
- Identify the most valuable data types. You want to only work with information that has a direct impact on your business. Leverage today's cloud offerings to manage such data without having to break the bank.
- Govern data well. Ensure that your architect is clear on the quality and relevance you want. Create committees to guarantee the quality of data.
- Create flexible systems. Building models that last are a more popular option for business owners. The best data architectures, however, are those that change with time. Such designs have no problem blending in with new solutions that are on the rise.
- Create a real-time data environment. Combine data warehouses and new approaches to ease real-time access to historical and current data. The idea is to ensure that decision-makers have everything to make spot-on decisions.
- Secure your architecture. Advances in data management systems have not been without a fair share of challenges. Threats from malware and viruses are always lurking. These threats come from different places, meaning that you'll need to be on high alert to keep your data intact.
- Use data as a service. Data as a service ensures that you can integrate all your systems with ease. This service works like software as a service (SAAS) solutions that lighten your work with different software. Create an internal cloud and offer your organization's decision-makers access to customized solutions.
- House all the components in a general system. A master data management strategy allows your firm to adapt to acquisitions, mergers, and realignments. You will get rid of any duplications from parallel databases and keep your business goals.
- Provide customized solutions. Management doesn't have to depend on IT before calling the shots. Business owners can use front-end interfaces to run queries and get prompt results. The tech guys will then specialize in security and data governance.
What are the benefits?
Here's how good, modern architecture will change your organization for the better.
- Enhanced Integration – Your organization needs to combine scattered information to get accurate business insights. A good data architecture enables stakeholders to weave through information with ease, picking out relevant input from different data sets. With a converged architecture, your organization may well be on the way to more innovation and better creativity. An efficient data integration strategy will take care of migration, conversion, and connection of different data points.
- Increased efficiency with dynamic platforms – Cloud and Edge Computing, among other technologies, have ensured that organizations can share data within the different sections. With good architecture, you should be able to fit such technology into your systems.
- Support for diverse data. A system that handles different data types with ease allows you to leverage robust, newer technologies. Good Architecture is flexible. This characteristic allows your data management team to transform data into various forms.
- Easier evolution of your products. From Redshift, Snowflake, BigQuery to Azure SQL Database, the technology landscape is always on the move. Newer and better technologies continue to see the light of day. Data architecture ensures that your organization keeps in step with emerging technologies. The onus is on organizations to ensure that their systems are robust enough to adapt to such technologies.
- Better storage management. Cloud systems have offered great storage solutions for your organization to leverage. The trade-off between computing and storage has become much easier.
Steps to Designing a Data Architecture
Now that we have a good idea of what data architecture would entail, let's look at the steps that go into creating one.
1. Have a data strategy in place
Before setting up your organization's data architecture, you'll need to be clear on your data strategy. An ideal strategy will show how you intend to use data to influence your business. In the words of Donna Burbank, Global Data Strategy's MD:
"Your organization's business model and strategy inform the direction you take as you create your data strategy. The data strategy then gives you a clear picture of your client. You should be able to tailor your product line to fit the needs of the customer. You get to improve customer service in the long run."
For an upturn in an organization's business impact, elaborate data infrastructures are necessary. The data strategy highlights all the areas that can influence the business' performance. Your data architecture is part of the whole strategy.
Your data team can use information in data architecture to strengthen your strategy. So while the architecture stems from the plan, its components inform the output of the policy.
2. Decide how you'll govern data
Data architecture minus data governance is a recipe for failure. Members of your organization can change the architecture to meet their end of the business strategy. Diverse viewpoints receive part of the blame for such changes. While these variations may look harmless at face value, your organization won't make the most of the strategy.
With Data Governance, you get to ensure that everyone uses data in the right way. Data governance also ensures that your architecture goes beyond the technical infrastructure. The practices and processes around data usage become centralized.
You need your data strategy to handle the organizational culture. This feature goes beyond clear operational technologies. Data governance supports your strategy in this regard. The governance strategy will touch on roles, responsibilities, and compliance matters.
Governance ensures that any upfront errors do not impact the whole process of handling data. Good data governance also reduces the risks of errors from start to finish.
3. Connect the architecture to data modeling
It is becoming clearer that you shouldn't design your data architecture to work in isolation. The data strategy guides you on what to include in the architecture while data governance allows you to make the most of the architecture. One thing is still missing – a description of how different parts of the data ecosystem interact.
Data modeling covers you in regard to data relationships. You'll get a clear picture of how data structures in different databases work together. Data models ensure that architects use various components to improve business outcomes.
With the models, you won't miss out on any of your data assets. From the entities to the attributes and relationships, your team will identify weak links with ease. In case the team finds any issues, they won't have a hard time resolving such. In a workflow diagram, the dotted lines represent the interactions between the parts of the data architecture.
Data Architecture in the Cloud
The cloud is an excellent solution for storing your data architecture. Cloud technology provides scalable and flexible storage solutions that allow companies to make the most of their resources while confidently knowing they can scale up or down as needed.
Designing a data architecture for the cloud
When designing a data architecture for the cloud, there are three key things to keep in mind:
Build on your existing technology and infrastructure
Cloud services can be designed as an extension of current systems, which reduces risk, cost, and complexity. Ensure that you use tools such as virtualization or automation to help manage security concerns across all platforms.
Agility is king
Data architectures should provide rapid access to information with minimal effort so employees can focus more time on their work instead of waiting around for slow systems. Designing a scalable system from the start ensures you don't have any problems when working at scale by maximizing performance while minimizing costs through load balancing servers based on workloads.
Be secure from the ground up.
Protecting your data architecture requires a clear understanding of each component's role in securing information. You should always have security at the forefront by following best practices from initial design concepts through infrastructure deployment and into day-to-day operations. This ensures that anyone involved is aware of their responsibilities when it comes to protecting critical company resources.
Security and privacy implications of data architectures in the cloud
Whether you choose to build your data architecture in the cloud or on-premises, it's critical that employees and customers feel their personal and sensitive information is well protected. This means ensuring security measures within every aspect of your system, including who has access to what data when they need it. A breach can cost an organization dearly, so good quality software with robust encryption will help protect against outside threats while limiting internal risks. Data architectures should also be regularly reviewed for compliance requirements, such as meeting industry standards around privacy management. By demonstrating sound governance over how customer data is managed, companies can increase trust, which leads to more business opportunities throughout different markets worldwide.
Advantages of data architecture in the cloud
Data architecture in the cloud is a cost-effective solution that allows companies to access scalable resources and solutions based on their changing needs. Being able to manage your data architectures without needing specific hardware or software licensing means you can get started quickly with no IT overhead, letting you focus on growing your business.
The top benefits of data architecture in the cloud are:
- Cost-effective: Not having to invest in specific hardware or software licenses allows companies to save money and use that for other purposes such as hiring more employees, expanding into new markets, and growing your business.
- Scalable resources: Data architectures scale up and down based on changing demands, so if demand increases, you can easily add capacity by provisioning additional servers without the need for costly investments. You also have access to an unlimited amount of storage which means no limits when it comes time to store all those big data files.
- Manageability: Cloud services are designed with manageability in mind making them more accessible than ever before, allowing any company, regardless of size or industry sector, to employ their benefits. Managing security becomes a lot simpler due to centralized authentication, authentication, authorization policies, and unified access control.
The future of data architectures in the cloud
With the rise of big data, cloud technology has emerged as a powerful solution for storing and analyzing large volumes of information. As companies increasingly look to extract value from their data architecture, new technologies are being developed which allow customers to manage all aspects of their infrastructure more efficiently.
Cloud architecture allows companies to be more agile and flexible when scaling up or down as needed. This will enable you to focus on the most critical parts of your business instead of spending valuable time building infrastructures that may never go beyond a certain point.
In essence, data architecture helps your organization chart a way for the next couple of years. This component of the business also enables you to choose the best technology to pick for the greatest success. Remember to make provisions on how well you can integrate these emerging technologies in the data architecture.
With all this information in mind, you need a partner that will help you govern your data for your data flows. Such partners help you to enhance the efficiency and accuracy of your architecture. If you need a tool to integrate with your data, try Integrate.io. Integrate.io is a cloud-based, code-free ETL solution that provides simple, visualized data pipelines across a wide range of sources and destinations. To set up a demo and a free 7-day trial, contact us here!