Data is everywhere and increasingly affecting more and more of a company's processes and business operations. Managing the enormous amount of data and the growing business need for data usage can be a significant challenge for many companies. As a result, data can feel like a costly burden rather than a value creator that supports better business decisions and creates deeper customer and market insights.
A data platform is a combination of tools that enable companies to collect, store, process, analyze, and access data in a structured and transparent way. The platform allows for the maximum value to be extracted from data and creates the foundation for a data-driven organization. twoday kapacity recommends a data platform built on a cloud-based data architecture, which ensures a flexible and scalable solution that is robust for future needs.
A data platform is essential for companies that have ambitions to optimize the value of data. This is because the data platform supports the company's processing of data from start to finish, resulting in a standardized and consistent way of processing and presenting data to end-users. Additionally, it embraces a secure way to manage user rights and access to data, ensuring that users can only access the data that is relevant to their needs and roles within the company. As a result, data is maintained centrally, avoiding multiple handling of data in different parts of the company, in different ways.
The data platform covers the entire value chain of data, which includes the functional support of the process from data collection, the use of structured as well as unstructured data, processing and analysis of data, and the presentation of data to end-users. Therefore, the term data platform is often used as a collective term for a range of components with different purposes and functions that can be combined depending on technical and business needs.
In broad terms, a data platform supports the following business processes:
Components for collecting and acquiring data for the platform. Often referred to as "Data Ingestion".
Components for storing and archiving data. Often referred to as "Data Store".
Components for processing, transforming, and enriching data. Often referred to as a "Data Processing".
Components for exposing and making data available. Often referred to as "Data Access".
As previously described, the data platform is the fundamental foundation that encompasses a wide range of components, each addressing a specific need. The components of a data platform together create a range of synergies that maximize the business value of data.
The architecture and components used in a modern scalable data platform are far from set in stone but depend on several different factors. Here are some of the most important factors:
However, many components largely make up the backbone of a modern data platform. They are all intended to reduce the complexity of operations and ensure high scalability and flexibility, while also ensuring a cost-effective platform. The core components that are activated by default are:
Previous IT and data architectures are often challenged by a fragmented data landscape, where data is located in different systems and "data silos". At the same time, the amount of data is increasing, technical complexities arise, performance declines, new tools and user needs to emerge, and the importance and need for data for business decisions increases.
This is where a data platform comes into the picture...
A data platform plays a central role in an organization, as it provides a central data foundation that is both flexible and scalable. At the same time, it allows for the use of the best analysis tools across different user groups.
The advantage of a flexible data platform is the ability to seamlessly connect new data sources over time, use new data types, or use new components from the platform's ecosystem - without starting over. It provides architectural freedom that is essential to avoid being "locked in" as an organization.
Regarding scalability, the benefits of a modern data platform include the ability to both scale up and down resources as needed. This means that resources can be scaled up at specific times or based on telemetry - quickly, on demand, and without major phase costs. Conversely, resources can also be scaled down when they are not in use or when the need for a resource decreases - thus saving operating costs. The advantage of scalability goes both ways.
All in all, a data platform provides companies with a foundation built on functionality and flexibility. In this way, a modern data platform becomes the cornerstone of the data-driven agenda.
There are many business benefits to implementing a data platform, as it ensures a structured and transparent way to use and create value from data. Below are some of the most important value creators for the business described:
When investing in a cloud data platform, high capital expenditures associated with purchasing and maintaining software and hardware are avoided. By moving the data platform to the cloud, companies only pay for the services they use, which is often a much more cost-effective way to operate their IT and data infrastructure.
The concept includes the possibility for end users, without technical expertise, to access data and create their analyses. The platform ensures a structured and secure management of self-service in the organization, where end users can access and analyze data in a fast and efficient way - to support better business decisions. It is implemented so that users achieve the desired flexibility, while IT has ownership of the process, ensuring high data governance concerning user rights and access to data.
It is easy to add new data sources and components, making the platform highly flexible. This is an essential feature as the development of working with data is constantly evolving, influenced by increasing data volumes, different data types, new systems, and technologies. Thus, the data platform ensures that the company can meet end-users constant needs for new analyses and insights based on new data sources.
A modern platform enables more efficient collaboration across the organization by providing common tools where different roles in a data project can work together.
When companies have control over the entire data journey from start to finish, it will provide end-users with access to in-depth insights into data, which will create an optimal foundation that can be used to make important business decisions based on. The data platform will enable end-users to perform in-depth analyses and make quick, fact-based decisions. This will create a data-driven culture where data is an integrated part of workflows, which will motivate users to rely on data rather than their gut feeling.
The technical advantages largely overlap with the business advantages, particularly in terms of the scalability and flexibility of the platform. Below are some of the most important benefits of implementing a cloud-based data platform:
These are terms that we might as well get used to. In general, the acronyms refer to the concepts of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The effects of using services under one of these three types include savings in time, cost, and effort for both the business and technical resources. Services under the three types contain more built-in components and functions, which help to free up time for analysts, data scientists, and data engineers, allowing them to pursue more value-creating data projects in the organization.
These are some of the keywords in a modern data platform. A cloud-based solution ensures high uptime and secure access to data through functionalities such as geo-replication of data, point-in-time recovery for data restoration, and much more. At the same time, a modern cloud-based data platform provides much better monitoring capabilities of resources through advanced event and consumption monitoring services, which can contribute to better resource planning and automated scaling.
One of the most significant benefits of a cloud-based data platform is the ability to easily and efficiently scale up and down and introduce new services based on business requirements. New services can be added quickly and easily as needed (on-demand self-service), and old services can be removed if they are no longer in use. This means that the organization needs fewer resources and less time for the operation of the technical platform.
A cloud-based platform enables a much higher degree of automation of development and maintenance tasks through the use of APIs and integration points. This allows, for example, the automation of adding new data sources, managing and scheduling job runs, scaling resources, automatically generating development code, managing security, and much more. Automating processes can also contribute to better governance of data and assist in creating valid master data - including contributing to ensuring the "golden record".
Do as a large number of the country’s most ambitious companies:
Fill out the form or get in touch with Søren – then we can have a chat about your challenges and dreams.