Studies show that most organizations use less than half of their data for business intelligence and decision-making. In today’s data-driven world, this is a worrying trend — it means that over 50% of businesses miss out on the market opportunities and other benefits that come with proper data analysis.
So, what’s the problem? Is it the current influx in the amount of data generated daily? Or is it that most executives are yet to understand the potential value of data analysis?
Well, while these could be some of the causes, the primary reason is that several organizations still rely on outdated technology, clunky processes, unresponsive policies, and rigid models for data management. Simply put, the main problem is the architecture that most businesses use to collect, transform, distribute, manage, and analyze their data.
This article highlights how hiring competent LATAM data architects can help resolve this issue and explains the importance of proper data architecture to modern-day businesses. It also delves into the future of data architecture and explains how to stay current with emerging trends.
Your Data Architecture Is More Crucial Than the Data Itself
“Data is the new oil.”
You must have heard or used this phrase a million times. Right? The big question is — what does it actually mean?
When most people describe data as the new oil, they refer to its intrinsic value and ability to help businesses understand prospects, streamline workflows, and identify market opportunities. However, just like oil, data also requires proper handling and processing to attain its optimum value.
And this is where the problem comes in…
Organizations today operate in an era of data deluge. Over the last few decades, the amount of data generated and collected globally has grown tremendously. From customer interactions to supply chain operations, every facet of business operations produces streams of valuable information.
Ideally, the data boom is supposed to result in better insights into target markets, inspire more informed decision-making, and create more strategic opportunities. However, it turns out it’s resulted in the exact opposite — most businesses are swamped with large data volumes that they barely use.
This is why data architecture is more crucial than the data itself!
A well-structured, modern data architecture can not only help your organization collect, store, transform, and analyze its data more effectively but also streamline the distribution of the derived insights. Without it, you’ll continue spending more and more on vast databases without any substantial ROI.
Enabling Faster, Real-Time Access to Business Intelligence
In most businesses without data architects, IT teams have almost full control of the data flow. They handle everything from collection to gleaning and visualization. If you’re running such an organization, you know how challenging it can be to access different data streams. Typically, you’ll have to submit a request to the IT team and await approval (which might take days or weeks if you have a small, overwhelmed IT department). Sometimes, the first delivery might not even be what you wanted, forcing you to submit another request and wait longer. By the time this back and forth is over, the data you requested might not be as fresh and valuable as it was before.
Does the above scenario sound familiar? If so, you’re facing a serious data architecture problem.
Data architects do not control the flow of organizations’ data. No. Instead, they streamline data processes to allow everybody to access whatever information they need whenever they need it. Doing so can help your teams make faster, data-informed decisions, enabling them to identify and leverage emerging market opportunities ahead of competitors.
Data Architects vs. Data Engineers
A data architect serves as the visionary behind the design and implementation of corporate data systems, ensuring that businesses can harness the power of their data to achieve strategic objectives. Unlike data engineers, they don’t implement already established visions and specifications. Rather, they conceptualize and visualize frameworks and develop data processing models and policies from scratch. Their primary objective is to align organizations’ data infrastructure with their business needs. As a result, data architects are often higher-level experts and more experienced than engineers.
Can your existing in-house data engineers double up as architects?
Well, it depends. If they have a background in data architecture, they can. If not, it might help to hire dedicated architects. And reasonably so — data architects usually handle more than just systems design, implementation, and maintenance.
Below are some roles of data architects that might not be in a typical data engineer’s job description:
- Translating business needs into data infrastructure requirements: The most crucial role of data architects is to ensure that organizations’ data systems and processes address their business needs. Sometimes, this might involve analyzing existing infrastructure to identify optimization opportunities. To achieve this, architects often require stronger business acumen and more extensive experience in data management than data engineers.
- Designing and enforcing data governance policies: Another crucial role of data architects that typical engineers might not handle is developing policies for data governance. These specialists are often responsible for the creation and documentation of data management expectations, procedures, responsibilities, and objectives for all the teams in an organization — including for other data personnel like engineers and analysts.
- Developing internal data security standards: Because of their crucial role in facilitating real-time access to data for all teams, architects also often establish policies to ensure sensitive business information doesn’t land in the wrong hands. This role involves determining the requisite degrees of protection for different datasets, defining access protocols and information-sharing policies, setting retention and disposal schedules, and establishing records management standards. In most cases, these specialists also work with security teams to ensure the organization’s data processes and systems comply with industry safety and privacy regulations.
A Glimpse Into the Past, Present, and Future of Data Architecture
As the data landscape evolves, so does the corporate data architecture. Here’s a rundown of some crucial milestones in this evolution.
First Generation: Enterprise Data Warehouse Architecture
Before the 2000s, most organizations relied on on-site Enterprise Data Warehouses (EDW). This architecture was defined by extracting data from operational databases and external sources, transferring it into a centralized in-house storage system, transforming it into a universal schema format, and enabling access via SQL-like queries. While the approach was perfect then, it was too rigid, making it challenging for businesses to handle their increasing data volumes. Also, it didn’t account for the fact that different departments often have varying business needs and require different data formats.
Second Generation: The Emergence of Data Lakes
The data lake architecture emerged in the early 2010s. While it still used the concept of centralized data repositories, it stored the data in its original form, allowing engineering teams to create customized “zones” for different departments. Its departure from the upfront transformation approach made it perfect for training ML models (which usually require data in its original form).
Third Generation: Cloud Data Architecture
As the need for speed and real-time data access grew, businesses started transferring their data infrastructure to the Cloud. The Cloud data architecture enabled organizations to converge data lakes and warehouses into one technology that could hold infinite volumes of data. It also supported real-time access and set the foundation for edge computing. However, unlike the first two generations, it’s very sophisticated, forcing businesses to hire hyper-personalized data engineers.
Fourth Generation: The Era of Distributed, Decentralized Data Ownership
The most recent milestone in the evolution of corporate data architecture is the emergence of the data mesh technology. This architectural framework involves unifying disparate data from different sources in a centralized database and enabling decentralized access through unified governance. It enables businesses to retain control over how teams access and share data while simultaneously streamlining data access.
Stay Ahead of Emerging Trends With Competent Latam Days Architects
Data architecture is still evolving. We are likely to see an increasing demand for decentralized data systems, more adoption of data fabrics and real-time processing, and the emergence of a ton of other new technologies that we could have never imagined. As the field continues to advance, the need for competent data architects is critical.
LATAM, with its extensive pool of highly qualified software and data experts, is a prime destination for hiring competent data architects. The region has a long history of supplying US and Canadian organizations with top-tier tech talent, so you don’t have to worry about straying into uncharted waters. Its proximity to North America, high English proficiency, and timezone alignment make it perfect when hiring architects for projects that require real-time collaboration.
Ready To Take The Leap?
Let DevEngine help you get the best LATAM data architects as you focus on other tasks. We are not just another hiring company. We are a client-centered firm that works with the best software and data specialists in Latin America.
When hiring through us, we can handle everything from job posting to recruitment, resume screening, interviewing, practical assessment, onboarding, and staff management. All our services come at reasonable, upfront prices. Also, unlike several hiring firms, we only work with a few customers at a time and allocate dedicated data architects for each client. This approach ensures that our active customers get full attention and hyper-personalized services.
Schedule a call today, and let’s discuss how to take your business intelligence to the future with competent LATAM data architects.