
Unlocking value through a good data management strategy
Setting the stage for AI
A solid data strategy—that is, how data is collected, stored, managed, and analysed to achieve business goals—is the foundation of any successful AI project, because the real magic and value of AI technology happens when it starts with your own data. Every business has different data sources, needs, and goals, but the common element is that before a new technology like AI can deliver value, you need to set the stage for success.
In fact, a recent Forrester study found that 35% of technology decision-makers said data will be their primary business in 2024, followed by 32% who will prioritise infrastructure modernisation. This insight shows that while organisations are embracing the latest trends, they are also prioritising the work needed to integrate them.
Every AI strategy starts with data
Almost every conversation about technology today includes generative AI. It’s important to remember that the key foundation is data and the effectiveness of it relies on the accuracy and accessibility of the data on which the AI models will be trained.
AI models cannot produce the right results without high-quality data. Improving your data quality enables machine learning models to accurately identify underlying patterns, thereby improving predictions. When organisations prioritise data quality through rigorous measurement, evaluation, continuous monitoring, and improvement, they not only improve model reliability but also reduce the risk of biased or erroneous conclusions. This improvement in model accuracy translates into cost savings, improved business outcomes, and a better competitive advantage.
Data that works for you with confidence
A system with inaccurate, misleading, or partial data will cause integration to fail. It is therefore essential to ensure that your data is flawless and reliable. Data quality is the responsibility of everyone in an organisation. At Hitachi Solutions, we find that many customers overestimate the quality of their data and underestimate the effort required to restore it.
Ask yourself the questions:
- What data do I have?
- Where are they?
- Are they accurate?
- Can people access the data they need to make the right decisions?
- Are they secure?
If you answer “no” or “ I don’t know ” to any of these questions, chances are others in your organisation will too.
Having a complete data platform
Modernising your data platform is the right place to start. A comprehensive cloud-based data and analytics platform unifies all your data, transforming and optimising it into a more accessible, usable, and valuable form. It’s essential for organisations that want to do more with their data and it is the foundation for core applications for using advanced analytics and business intelligence.
Modernised data platforms also enable people to access the information they need, regardless of where the data resides, and provide all the necessary technical documentation – data acquisition, cataloging, lineage and security.
Many data platform providers have moved to modernised “lake house” architectures that automate data ingestion and loading, query optimisation, resiliency, data protection, and data access. These architectures are “open format,” meaning the data they contain can be accessed and processed by a variety of tools and systems. They address the challenges of processing large and diverse data types and formats in a scalable and efficient manner, and address the growing complexity and volume of data across all industries.
Having a platform that provides the right governance, integration, security, and data quality aren’t just best practices; they’re necessary for business success, and they lay the foundation for you to start leveraging data, applying AI and therefore transforming your operations.
Integrating disparate data
Generative AI is most effective when it has structured and unstructured data, both internal and external, to process. As the use of generative AI increases and companies deploy more conversational experiences for customers and employees, “the amount of unstructured data managed by companies will double by 2024”, according to Forrester. To scale, companies must double their infrastructure, with all-in-one unified data platforms such as lake-houses to manage costs, support multi-structured data analytics, and enable broader use cases and workloads.
A robust data platform like Microsoft Fabric brings together data and analytics tools, including AI capabilities, into a single, unified product. This is a much-needed solution in the data platform space when it is not practical or cost-effective to deploy multiple, disparate tools for secure cloud applications.
For example, manufacturing companies use Fabric to unify operational data (like plant sensor information) and ERP data (like inventory levels). It’s a true unified database that can facilitate advanced analytics. It also helps eliminate long-standing data silos and create a more collaborative and cohesive work environment.
Why do so many data initiatives fail?
Initiatives sometimes fail, not because the technology isn’t right, but because organisations don’t foster a culture where employees are encouraged to use data in their decision-making processes .
Data modernisation programs are not the sole responsibility of IT departments, but are tightly integrated with an organisation’s talent, resources, and processes. If staff are not engaged and do not understand the expectations for how they are expected to work with data and extract it for business intelligence, challenges are almost certain to arise.
With our digital innovation service , we help our clients define, prioritise and value each modernisation initiative.
Where to start?
Having the right data means you can start leveraging ML and AI today to predict what your customers will need tomorrow. But there’s no one-size-fits-all solution. Because every organisation is unique, it’s important to start by asking the right questions from the start. Data quality, infrastructure, operational procedures, and change management are just a few of the factors that will determine success.
Hitachi Solutions is a global solutions integrator specialising in Microsoft technologies. With years of experience, we deliver end-to-end business transformation through consulting services, industry and technology expertise, and proven implementation excellence. Our goal is to support and accelerate data and business modernisation initiatives that drive value for our customers. So to start, you’re at the right place!
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