Data Services
Modern data platforms play a crucial role in helping organisations to make decisions, deliver core services, evolve their strategies and achieve their growth targets. As such, it's essential for any forward-thinking organisation to invest in a data infrastructure that will serve their needs, both now and in the future.
At Methods Analytics, we specialise in building secure, high-performing cloud data platforms for organisations from all sectors. Our team of experts understands your context, use cases and constraints, enabling us to focus on efficiently building only what you really need.
We have the practical experience to work through the complexity of your legacy data estate, the nuance of your user requirements, and a deep understanding of the specialist governance considerations for particularly sensitive data. Our collaborative approach will give your team practical experience to get the most out of your data platform from the start.
To learn more about how we can build your cloud data platform and address your data storage requirements, get in touch with us today. We will advise you on how to implement a platform that will deliver lasting value as the beating heart of your data transformation efforts.
In the realm of data management, one size doesn't necessarily fit all. Every organisation has unique needs, goals and constraints, requiring a tailored approach when implementing new data tools. We understand this, and that's why we offer a comprehensive suite of data platform services designed to meet your specific needs.
Take a look at the key data platform services we offer to help you harness the power of your data and transform it into actionable insights:
We specialise in building secure, performant cloud data platforms, ready for integration with modern AI tools. Our customer data platforms are designed to handle the complexity of your legacy data estate, the nuance of your user requirements, and the specialist governance considerations for particularly sensitive data. We focus on building only what you really need and doing so efficiently, saving you time and resources.
As your data grows in volume and complexity, maintaining service levels can become a challenge. Our data warehouse health check service is designed to help you overcome this challenge. We can help you reduce data ingestion and processing times; ensure your database and data models are optimised for reporting and analytics; review security and data retention to ensure adherence to GDPR; and revise access to data to deliver a better user experience.
Data lakes provide a flexible, scalable solution for storing and analysing vast amounts of raw data. We can help you set up AWS-powered data lakes that can handle the scale, agility and flexibility required to combine different data and analytics approaches. This allows you to gain deeper insights than with traditional data silos and data warehouses.
No matter what your data needs are, we'll leverage our practical experience and deep understanding of data management to provide you with a data platform service that truly meets your needs. Whether you're just starting your journey to the cloud, or are looking to expand the capabilities of your well-established DevOps teams, we'll integrate with your processes and build your cloud data platform at a pace that works for you.
A data platform is a sophisticated, technology-enabled environment that provides an integrated and unified view of an organisation's data. It is the foundation upon which data from various sources is consolidated and managed. But what does this mean in practical terms?
In the simplest sense, a data platform is a place where data is collected, stored, processed and analysed. However, in the context of modern business operations and the digital age, a data platform is much more than just a storage facility for data. It's a dynamic ecosystem that enables data to be transformed into actionable insights, driving strategic decision-making and providing a competitive edge.
A data platform is designed to handle a wide variety of structured and unstructured data types. This includes structured formats such as databases, semi-structured data types like XML files, and unstructured data including text files or social media posts. A modern data platform needs to provide the infrastructure necessary to store, process and analyse this data at scale, enabling businesses to derive meaningful insights from the reams of information available to them.
But a data platform is not just about technology. It also involves the processes, methodologies and strategies used to manage and use data effectively. This includes data governance, data quality management, data integration, data security and more.
In essence, a data platform is the brain of your data strategy. It should be designed to learn the context of the world around you, ready to help you make better decisions. It's the key to unlocking the full potential of your data, turning raw data into valuable insights that can drive business growth and innovation.
A data warehouse is a crucial component of your overall data platform infrastructure, acting as a central repository for all your structured data. However, as the volume and complexity of data increase, maintaining service levels and managing costs can become challenging. We offer a comprehensive data warehouse optimisation service to help you overcome these challenges in the following ways:
Reducing data ingestion and processing times
The first step in optimising your data warehouse is to reduce data ingestion and processing times. This involves streamlining the processes used to extract, transform, and load (ETL) data into your data warehouse. Our team of experts can help identify bottlenecks in your ETL processes and implement solutions to speed up data ingestion and processing.
Optimising database and data models for reporting and analytics
The structure of your database and data models can have a significant impact on the performance of your data warehouse. We can help ensure your database and data models are optimised for reporting and analytics, enabling faster query performance and more efficient data analysis.
Reviewing security and data retention to ensure adherence to GDPR
Data security and compliance are critical considerations for any data warehouse. We can help review your data security measures and data retention policies to ensure they adhere to GDPR and other relevant regulations. This not only helps protect your data, but also reduces the risk of non-compliance penalties.
Revising access to data to deliver a better user experience
We can help you manage access to data, ensuring that users can easily access the data they need, when they need it, without compromising data security. By improving data accessibility, we can help your team make more effective use of your data warehouse.
By taking advantage of our data warehouse optimisation service, you can get the most out of your enterprise data platform. Whether you're looking to improve performance, enhance security or improve user experience, we have the expertise and experience to help.
A data lake is a storage repository that can hold a vast amount of raw data in its native format until it is needed. Unlike a hierarchical data warehouse, which stores data in files or folders, a data lake uses a flat architecture to store data. Each data element in a lake is assigned a unique identifier and tagged with a set of extended metadata tags. When a business question arises, the data lake can be queried for relevant data, and that smaller set of data can then be analysed to help answer the question.
Choosing the data lake approach for your customer data platform delivers a number of key advantages for your data strategy:
In this way, data lakes provide an intuitive environment for the processing and preparation of diverse data types, making it easy to use machine learning and data science methods directly using this raw data. This will give you the opportunity to generate new understanding about your business and customer base.
We can help you integrate data warehouses into the data lake model, ensuring that the data warehouse receives the output from the data lake, and that data consistency is maintained across the two data environments. We'll make this process as straightforward and seamless as possible, helping you unlock the full benefits of the data lake.
A modern data platform is more than just a place to store data. It's a comprehensive solution that enables organisations to harness the power of their data and transform it into actionable insights
Here are the key components of what a modern data platform looks like, and what it needs to be effective:
A modern data platform should be seen as a complex ecosystem that brings together a wide range of technologies, tools and processes. It's not just about storing data; it's about making data work for you.
Choosing the right data platform for your organisation is a critical decision that can significantly impact your ability to leverage data effectively. In order to make the right decision, you'll need to consider the following factors:
The best data platform for your organisation depends on your specific needs and circumstances. We'll work with you to assess what you need from your data management strategy, and deliver a tailored customer data platform that meets all of your requirements.
Implementing the right data architecture is crucial for managing and utilising data effectively. It involves designing and setting up systems to collect, store and manage information, in alignment with how you use data.
When implementing the right data architecture for your needs, you should consider the following:
Implementing the right data architecture is not a one-time task. As your business goals and data needs change, you'll need to continually review and update your data architecture to ensure it continues to meet your needs. We can help you with this, establishing a best-in-class infrastructure for data acquisition, processing and analysis, and reviewing its effectiveness on an ongoing basis to deliver lasting improvements.
Azure Data Services provides a set of fully managed relational, NoSQL and in-memory databases. These services automate tasks like configuring and managing high availability, disaster recovery, backups and data replication across regions. This automation saves you time and money, allowing you to focus on extracting value from your data rather than managing the infrastructure.
Azure Data Factory is a fully managed, serverless data integration service. It allows us to integrate all of your data, regardless of where it resides. With Azure Data Factory, we can create, schedule and manage data pipelines, transforming your data from disparate sources into meaningful insights.
AWS provides robust support for data lakes. AWS-powered data lakes, supported by the unmatched availability of Amazon S3 and Redshift, can handle the scale, agility and flexibility required to combine different data and analytics approaches. This allows us to build and store your data lakes on AWS, enabling you to gain deeper insights than with traditional data silos and data warehouses.
AWS Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyse all your data using your existing business intelligence tools. It delivers fast query performance by using columnar storage technology and parallel query execution. With Redshift, we can accelerate your time to insights with fast, easy and secure cloud data warehousing at scale.
We believe that a successful data platform is built on a deep understanding of your unique needs and context. As such, our approach is designed around four key steps - Discover, Design, Develop and Migrate - to ensure that we deliver a data platform that is secure, efficient and tailored to your specific requirements.
Here's how we do it:
Our expert architects and engineers will start building this context by working with your data and information asset owners, documenting your systems, rigorously cataloguing each entity and mapping the data flows into, out of, and within your organisation. Our user researchers will talk to your users, your teams and your executives, capturing use cases for the platform which will help you prioritise your development roadmap.
We’ve designed your platform for the AI-ready future of data, so we build for the long term. This means loosely coupled, best-of-breed data capabilities, with each engineered to be independently scaled or replaced, making maintenance automated and simple. We’ll build interfaces to be easily managed and readily extended, meaning your team can quickly ingest data from new sources as they become available.
Migrate: To start using your new data platform to make better decisions, you’ll need to introduce it to your first phase of data, users and integrations. We offer a comprehensive migration service to get you up and running.
Our experienced team will migrate your historic data into your new platform and make sure it’s modelled to enable your new capabilities to extract maximum value. We'll ensure your data is handled as if it were our own throughout, in compliance with your policies and in adherence with your governance regime. We’ll onboard your users and work with your other suppliers and partners, to bring them on board. Together, we’ll start rationalising your legacy data services system-by-system, and begin realising savings for your organisation.
Our approach is collaborative and focused on your needs. We work closely with your team, building a deep understanding of your context, use cases and constraints. This allows us to build a data platform that is not only efficient and secure, but also tailored to your specific needs and ready to deliver value from the start.
The council employs over 2000 staff who work to prioritise improving infrastructure and housing to support a growing, low-carbon economy; offer education opportunities that lead to the right skills and the right jobs in the right places; ensure clean and safe streets; improve public spaces and local culture; and helps people to help themselves, while always protecting the most vulnerable children and adult. As part of its pledge to compete at the forefront of digital innovation with a commitment to using
technology for positive change, the council wanted to improve organisational data management enabling it to more effectively use its data, lower costs and support new services.
If an item becomes obsolete, no longer in use or isn’t working, it’s either disposed of or sent to storage. Across DE&S, there was no set process to monitor and manage the disposal risk of these items. It was only being done at team level, tracked over non-interfaced electronic systems, local spreadsheets and paper-based registers.
Systems could not be linked. Confidence in the disposal process could not be recorded or understood.
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