The Data Leaders Checklist on Building the Enterprise Technology Stack

Building a technology stack can mean different things to different teams. There may be mixed reviews depending on who you ask.

Idealists may say their tech stack improves collaboration and productivity, but that on-ground may disagree depending on how onboarding and implementation were carried out. Financial professionals might cite all the monthly expenses associated with SaaS subscriptions the company relies on. In-house technology departments may dive into all the API integrations, frameworks, codebase, and front-end and back-end technologies. Data leaders say there’s no one-size-fits-all answer to picking the right tech stack for your project. But there are some factors to consider that can help you make the best decision for your use case. 

We asked data and analytics leaders the key factors when choosing solutions to build your enterprise tech stack. Here’s what they said; 

Launch the MVP quickly 

Billy Odera , Chief Data Officer at Jubilee Insurance

• Business capability: Your technology stack plays an important role at every stage of your business. If you are just starting out, your primary goal must be launching the MVP (Minimum Viable Product) as quickly as possible.
• Cost: Depending on your organisation’s size, the impact of cost can vary.
• Open-source community: When you need to find answers, it would be better to have access to hundreds of books, courses etc.
• Scalability: The ability to scale to the ever-growing heights at which data is collected is very important.
• Keep an eye on data sources and integrations to existing legacy systems.

Articulate the potential ROI 

Esther Munyi , Chief Data & Analytics Officer at Sasfin  

It is essential to articulate the potential return on investment and comprehend how the solution will address a business need or problem. Specialised knowledge and skills are necessary to build and maintain the solutions needing technical proficiency. Quickly changing markets necessitate solutions that can adapt, scale, and are compatible with modern architectures. Moreover, operating costs to maintain and upgrade the solutions should be considered.

To build or buy?

Hartnell Ndungi , Chief Data Officer at Absa Group  

As cloud computing continues gaining popularity, organisations must consider several key decisions before starting. The first is whether to utilise cloud or on-premises solutions. All data analytics and data science tools are now available on the cloud, making this an increasingly popular option. 

The second decision is to purchase an existing solution or build one from scratch. With the right data skills, enterprises can build a comprehensive data and analytics platform with descriptive and prescriptive capabilities. However, working with consultants or outsourcing may be the best approach for more complex solutions and platforms if the organisation is at a low data and digital maturity level. Furthermore, organisations should consider their business strategy, existing infrastructure, existing skills, use cases, data privacy guidelines, regulation, and leadership when making their tech deployment decisions.

Consider future fit for the org 

Kulani Likotsi , Head of Data Management and Data Governance at Standard Bank South Africa  

Start with the business objective or business case in mind. Ask yourselves what business problem you are trying to solve. Involving the right stakeholders upfront when making decisions about the technology stack, such as IT, Business, Data, Finance, and Human Resources representatives, is important. The business case will help guide which technology stack is necessary. Technology should be chosen to enable business solutions. Remember to find scalable technology within the company’s requirements and future growth opportunities. Leaders consider technology that is a future fit for the organisation, as it is expensive to change technology often. Ensure that there is seamless integration between the new and existing technology stacks. Continuously review and maintain the technology stack to ensure it is still relevant to the business strategy and meeting customer needs. Invest in staff support and training to maximise the technology stack and ensure the company has the right skill set.

Develop a strategic edge in understanding customers’ behaviour

Mohanaselvan J. , VP Data & Insights at Expo 2020 Dubai  

When building and investing in a technology stack, it is crucial to consider factors such as scalability, flexibility, interoperability, integration, security, reliability, cost-effectiveness, developer experience, future-proofing, alignment with business goals, and in-house expertise. We found that an optimal technology stack for our data & insights activities included AWS, Alteryx, and Tableau. This combination offered us a scalable and flexible infrastructure (AWS), advanced data processing and analytics capabilities (Alteryx), and powerful data visualisation tools (Tableau). These components seamlessly integrate with one another and align with our goals and strategy, contributing to the success of the Data & Insights initiatives during the Expo 2020 event.

However, there are some trade-offs to consider with this technology stack. While AWS, Alteryx, and Tableau are popular and widely used platforms, they come with higher costs compared to open-source alternatives. Additionally, although these platforms offer a rich developer experience and extensive documentation, they require specialised skills and expertise to fully leverage their capabilities, which was an area we had to scramble to recruit for before the event when we realised the skills gap, particularly with AWS. 

In conclusion, today, our technology stack is a well-rounded solution. It caters to current business objectives and needs while acknowledging potential challenges such as costs and the need for specialised expertise (which we have carefully nurtured with years of mentoring data scientists). By considering these factors and continuously adapting our technology stack, we developed a strategic edge in understanding our customers’ behaviour which offered opportunities for us to leverage key insights for success.

Create an adoption plan  

Olamide Jolaoso , Head of Data Analytics at Wema Bank Plc.  

The key considerations include the following:

• Long-term strategic goals of the company
• Business needs and objectives
• Business need vs value generation
• What unique problem is being solved
• Change management
• Digital adoption and data literacy of employees
• Cost and resourcing

Consider how to upskill human resources 

Peter Jackson , Chief Data and Product Officer at Outra  

• The first consideration is that technology alone is not the answer, it will need an operating model and often up-skilling of people.
• Then you need to consider what business outcome the new technology will deliver, which must be the success criteria you focus on.
• Any new technology in the stack must be using governed and quality-assured data, no point in using new technology and poor data.
• How does the new technology fit into the existing/legacy tech stack? Are you creating more complications and a ’new legacy’?
• What is the cost profile? Is it properly understood?

Integrate between data and stack 

Theo Groenewald , Head of Data Management at Discovery Limited  

Interoperability between data teams across the organisation, including integration between the data and tech stack, is paramount. The availability of skilled personnel and the associated costs must be considered, especially in South Africa. Moreover, data sovereignty must be considered whether cloud services are available in the region.

Can it help build end-user trust?

wessam Ahmed , Associate Director Enterprise Solution-Data Architecture at CIB Egypt  

Investing in or building solutions for your technology stack is essential to any business’s digital transformation journey. Here are some key considerations to keep in mind:

• Business Needs: The first consideration should always be the business needs. Identify the business requirements and objectives you want your technology stack to achieve. The technology stack should align with the company’s business strategy, goals, and objectives.
• Scalability: Consider the scalability of the technology stack. Ensure the technology stack can scale up or down per the organisation’s requirements. Choose a technology stack that is flexible and adaptable to the changing business needs.
• Interoperability: Ensure the technology stack can integrate with other systems or applications within the organisation. This will help to streamline workflows, reduce data silos, and enable data sharing across the organisation.
• Security: Data security is crucial in any technology stack. Ensure that the technology stack has appropriate security measures to protect sensitive data from unauthorised access, data breaches, and cyber threats.
• Cost: The cost of the technology stack is also an essential consideration. Determine the technology stack’s total cost of ownership (TCO) and evaluate the return on investment (ROI). Choose a technology stack that provides the best value for money.
• User Experience: Consider the user experience when selecting a technology stack. Choose a stack that is easy to use, intuitive, and user-friendly. The technology stack should help to streamline workflows, increase productivity, and improve user satisfaction.

Considering these key factors, you can select a technology stack that aligns with your business needs, is scalable, interoperable, secure, cost-effective, and provides an excellent user experience.

What does success look like?

Yomi Ibosiola , Chief Data and Analytics Officer at Union Bank of Nigeria , 

No single tech stack is perfect for all business projects, but certain factors can help make the best decision. We began by clearly defining our requirements and envisioning what success would look like. Then, we identified the platforms already used across the bank to make management, governance, and integration easier. Additionally, we engaged with and discovered the needs and expectations of our target audience, their digital literacy, and how it could affect our selection of tech stack. Moreover, we considered ease of use, learning curve, cloud versus on-prem architecture, cost of deployment and license maintenance, scalability, and security to make the optimal decision in selecting the right tech stack for our data projects.