TL;DR A modern data platform integrates the tools necessary to unlock data value at speed and scale while ensuring data quality and security. This article explores the benefits of using a modern data platform, key features, and considerations when choosing one, and the role a data consultancy plays in helping you get started.
At V2 AI, we have partnered with several data platform providers like Snowflake, Databricks, Microsoft, AWS, and Google Cloud to support our clients in building the solutions best suited to their business goals.
For example, we leveraged Snowflake on AWS to integrate data from two isolated legacy data systems for a leading game machine and game analytics provider. The solution simplified business intelligence reporting by 90% allowing faster, self-serve access to bespoke data insights and operational guidance. Our client is now able to improve machine performance, drive profitability, and strengthen its competitive position in the Australian gaming market.
Similarly, we utilised Databricks to provide predictive analytics foundations at a leading Australian university. On-demand insights replaced biannual reporting cycles, allowing for timely interventions to improve student academic performance and reduce graduation delays.
Your organisation can also achieve measurable business outcomes from a data platform rollout.
Benefits of Modern Data Platforms
Modern data platforms support the following business outcomes.
Enhance the customer experience
Real-time analytics puts data in the hands of those who need it most as soon as it becomes available. This allows organisations to respond quickly to changing customer requirements. For example, our university client’s early-stage predictive setup could only generate student engagement reports twice a year, delaying support mechanisms for students at risk of failing. With Databricks, they can now generate predictive insights on demand to provide timely interventions and improve customer outcomes.
Reduce operational costs
Data distributed across multiple systems can escalate operational costs due to redundant processing mechanisms and reporting complexities. Consolidating the data into a single platform allows you to leverage native capabilities, reduce bloat, and introduce efficiencies with more focus. For example, we consolidated data from eight different sources into Snowflake for our gaming client. Eliminating existing redundancy and reporting complexity brought annual savings of over 50%.
New opportunities for business growth
Integrated data analysis can reveal new opportunities not identifiable in silos. Our university client was able to correlate student engagement data with course content and quality to solve underlying curriculum and delivery issues and improve long-term performance. Our game machine client was able to generate new reports to identify market gaps and pitch their offerings more strategically. Data provided evidence to the sales team to eliminate guesswork and increase sales with confidence.
Security and compliance uplift
Data consolidation allows organisations to eliminate vulnerabilities and reduce patchwork security initiatives. Instead, they can leverage native security features to boost data security and compliance requirements. For example, data consolidation to Google Cloud’s Looker, another modern data platform, allowed a large retail client to resolve 600+ vulnerabilities within just three months.
Increased innovation capabilities
A modern data platform provides built-in capabilities for end-to-end ML/AI development, from model selection and training to deployment at scale. Organisations can use it as a foundation for future AI innovation, including for building autonomous AI agents that can access the data to automate complex business processes.
What Is a Modern Data Platform?
A modern data platform is a composable technology stack that allows organisations to collect and manage all analytical and transactional assets from a single, well-governed environment. You can ingest, store, process, and analyse data as needed, while implementing all necessary security and access controls for full compliance.
A modern data platform integrates data from across the organisation to eliminate silos, while also enhancing data usability. It enables self-service analytics so decision makers can quickly access the information they need to make optimal choices.
It also includes several integrated open source and third-party tools to handle day-to-day tasks in the data lifecycle, such as cleaning, streaming, security validations, transformations, and more.
Many modern data platforms go a step further to provide built-in ML/AI capabilities. They have features that allow you to train and run models from within the solution itself. They are often a key component of AI readiness within any enterprise, as successful AI initiatives require high-quality data to function as expected.
Components of a Data Platform
Traditionally, organisations used a data warehouse for structured data analytics and a data lake to store raw data at scale. Later on, data lakehouse architecture emerged to unify these approaches, combining the scalability of data lakes with the performance and governance of data warehouses.
A modern data platform is a data lakehouse on steroids. It has many components from traditional analytics to modern AI development, which all work together with minimum friction.
You can think of it as having the following layers.
Data storage | Includes access to scalable cloud object storage for all structured, unstructured, and semi-structured data. |
Data ingestion | Supports batch or bulk data ingestion as well as real-time data streaming from a range of sources |
Data transformation | Supports data processing and transformation to various types and formats, both before and after storage. |
Business intelligence and analytics | Includes tools for reporting, visualisation and analysis. |
Data observability | Provides monitoring capabilities like tracking, logging, alerting, and anomaly detection to promote data quality, availability, and reliability. |
Data discovery | Allows users to quickly find the data sets they need, including related and similar data. Modern platforms increasingly support data discovery and search through a natural language question-answer chat interface. |
Data governance | Includes built-in encryption, access controls, data lineage tracking, and other features that support data security and compliance. |
Metadata management | Data catalogues and other features that allow users to describe and summarise their data assets to support understanding, search, and discovery. |
Machine learning and AI | Includes built-in ML models, access to open source AI models, training and version control, as well as Ops capabilities to streamline model development and updates. |
The Role of Data Consultancy in Business Transformation
An experienced data consultancy partner ensures your organisation leverages the full capabilities of the new data platform, and the move to the new platform is smooth and hassle-free.
With several solutions available in the market, it can be overwhelming for organisations to choose the data platform that best meets their needs. They may also lack the internal talent and knowledge to leverage the data platform selected in a way that maximises its potential for their use case.
As a leading data consultancy, we possess expertise and experience in data platform development across diverse industries and technologies. We know how best to customise the most suitable data platform for your organisation’s requirements. We can plan project delivery from start to finish while also upskilling your existing team. Our unique data platform roll-out strategy enables your internal team to have hands-on involvement from the start, allowing them to take full long-term ownership of the new system.
Thanks to strong partnerships with leading data platforms, we can deliver cost benefits and premium support to ensure platform roll-out is on time, in budget, and does not disrupt existing business operations. We also have in-house accelerators (battle-tested solution templates) that can be further used to speed up your innovation projects to achieve measurable outcomes.
Contact V2 AI today to get started with your modern data platform discovery project.
