Transition to Elite Data Engineering
Transition to Elite Data Engineering allows performance driven processes with a clear goal to produce data that is available, usable and secure, through sustainable architectures and implementations, product thinking, and evolutionary design.
Our data strategy service is designed to help organizations unlock the full potential of their data, driving business growth and transformation. We work with you to understand your business needs, assess your data landscape, and develop a tailored data strategy that aligns with your organizational objectives. We understand that each organization has unique data needs, and we take a customized approach to create a data strategy that works best for you.
Firstly we begin with a set of workshops to understand the challenges you are currently facing and the goals you are aiming for.
We then conduct an in depth assessment - a comprehensive analysis of your existing data assets -to identify the gaps between the as-is and the target scenario we want to reach.
Finally, based on the insights gained from the data assessment, we define a customized and comprehensive data strategy, extensively covering the complete journey, from development to implementation and measurement:
- Tools & Technologies
- Execution plan
- Success Criteria
Within our Elite Data Engineering processes we recognize the importance of data governance and the crucial aspect it plays in a comprehensive data strategy.
It provides the necessary framework for managing data effectively and ensuring that it is used in a way that meets legal, regulatory, and ethical requirements.
A well-designed data governance framework helps organizations to manage their data assets better, improve decision-making, reduce risks, and gain a competitive advantage.
In case you are adopting a multi-cloud strategy, we can support you in designing the logical and physical implementation to create a smooth experience in producing and consuming data in such an environment. This approach can provide a comprehensive solution that addresses various data management challenges, such as scalability, reliability, and security. At Agile Lab we have specialized in developing products and solutions that follow the key concept of technology agnosticism, allowing our clients to avoid vendor lock-in, improve data security and manage costs more effectively.
Partnering with us for your data strategy needs means we help you transform your organization into a data-driven enterprise that is agile, efficient, and equipped to succeed in the digital age.
Our data architecture service aims to design the best architecture for each scenario: platforms, use cases, migrations, framework and libraries. Our team of experienced data architects works closely with you to understand your unique requirements and objectives, before designing and implementing a customized data architecture solution that aligns perfectly with your business goals. For example, design of a data lake may include the software selection for the platform vendor, data organizations, processes and team organization.
Our approach to data architecture is driven by a deep understanding of the business value of data. We prioritize the creation of data architectures that are flexible, adaptable, and future-proof, allowing you to respond quickly to changing business needs and take advantage of emerging technologies and data sources. That’s why, when designing an architecture, we always follow these fundamentals:
- Principles first: it is important that an architecture is guided by principles that must be aligned with the goals of the initiative
- Evolutionary: the architecture must extensible and evolvable along the time
- Performance: scaling, resiliency and optimization are crucial to lower costs and to create superior user experiences
- Security and compliance: it must be embedded in the architecture by design.
- Sustainability for the customer: we don't pick up fancy technologies or languages that are not maintainable or sustainable by the customer itself
- Automation: we hate manual operations, the architecture is always taking care of processes automation
According to your needs, our data architecture service also includes, data platform architecture and Implementation with both physical and logical architecture, definition of the tech stack and its integration patterns, definition of data science processes and their level of automation. The data platform can be designed either with a lakehouse, a DWH pattern or a Data Mesh, shifting towards a more developer centric experience.
We love to craft data or ML platforms, making the life of data teams easier. Our goal is always to reduce the cognitive load of users and improve and automate levels of governance. Our platforms are always trying to hide complexity to the data team embedding best practices in the platform layer.
Are you considering a platform migration for your business? Our team has extensive experience in migrating a variety of platforms, including operating systems, databases, and applications. We will work with you to understand your unique business needs and develop a customized migration plan that minimizes downtime and ensures data integrity.
Contact us today to learn more about how we can help you build a robust and scalable data architecture that will power your business growth for years to come.
Our team has years of experience in managing complex data environments, we commit on SLA, and we pride ourselves on our ability to handle the most challenging data projects with ease. Because of this, we don’t just take on basic requirements, but we try to understand which are the opportunities ready to be discovered, providing professional support 24/7.
Our team of experts is available around the clock to provide you with the support you need, whenever you need it. We commit on SLA, design pipelines, and model data to make it useful, valuable, meaningful and consumable for the users.
Which data services require a full, around the clock management for you? Whether that’s Cloudera Cluster or K8, with our management service, you can enjoy a streamlined and hassle-free approach to managing your data infrastructure.
Our team of experienced professionals will work closely with you to ensure that your clusters are optimized for performance and reliability. We proactively optimize your costs, provide end-to-end support, from installation and configuration to monitoring and maintenance, so you can focus on what you do best - running your business.
At Agile Lab we always aim for high quality software and Agile methodology: use case development is based on iteration and being part of a cross-functional team, in order to share goals and understand the functional domain.
We understand that every business is unique, and therefore, we develop each use case based on the requirements of business goals, handling every project end to end, no matter the technical, functional and environment complexity.
Our team will work closely with you to understand your business objectives, data sources, and pain points to develop use cases that address your specific challenges.
We adopt a development workflow - embedding all the data engineering, devops, dataops and data science best practices – that involves a series of steps, divided in three main parts:
- The first part involves the discovery, ideation, and prioritization of the use cases based on their potential impact on your business and the feasibility of implementation.
- The second part is about design, development and testing, to ensure use cases are accurate, scalable and reliable.
- The final part is about deployment and monitoring, providing the necessary training and support to ensure that your team can use projects effectively.
We have experience in helping organizations to implement a variety of project types, such as DIH to offload data from operational systems and to create denormalized views ready to be consumed from the digital channels, or MDM focusing on the disambiguation among several copies of the same informative unit, such as the customer that can be present in several forms and in various systems in a big enterprise.
We develop use cases that showcase the benefits of mainframe offloading, including increased speed, scalability, and cost-efficiency, as well as streaming, in order to help organizations process and analyse data in real-time, allowing them to respond quickly to changing business needs. We are experts in several data integration techniques (API, batch, real time, etc.), to wire your data strategy with the overall IT ecosystem.
In terms of data pipelines, we can focus on DataOps to help organizations manage and automate their data workflows, MlOps, to quickly and easily build, deploy and manage machine learning models, and optimize data pipelines and data structures to reduce the amount of computational resources needed, leading to minor cost but also to minor CO2 emissions.
Contact us today to access to a team of experienced professionals who will work closely with you to develop use cases that are tailored to your specific needs.