There are plenty of articles talking about how companies can analyse their data at scale. What tools they should use to leap into their lakes of data and what solutions are on offer to ensure the data is secure, clean and relevant. Few answer one very important question first – why? Why does your organisation need to analyse data at scale?
The first answer comes from Gartner – artificial intelligence (AI). The sheer scale of AI innovation and solutions means that companies need solutions that ensure their data and analytics are cost-effective while delivering on data reliability and reduced complexity. Forrester believes that for the small to medium enterprise, there are ‘significant gains by employing a smart, comprehensive data analytics program’. For Mint, it is about placing the organisation at the forefront of data and analytics so it can better access, manage and act on its data.
Visibility through the cloud
Microsoft Azure is designed to empower the business, giving it tools that allow for your organisation to store, process, analyse and visualise data from across multiple sources and formats. The highly agile and modern architecture ensures organisations can leverage advanced technologies such as AI and machine learning and big data processing, and that they can do so with relative ease.
How? Well, here are five reasons why Azure is your data skeleton key (to unlock your potential and business):
1. Azure Synapse Analytics gives organisations the option to store your data in multiple formats that include Parquet, Delta Lake and CSV. The format you choose will depend on the performance you need and your storage cost expectations.
2. You can use Azure Data Factory to automate and manage your data workflows, so your data is consistently and accurately transferred from multiple sources into Azure Synapse. You can use data pipelines to manage your complex data integration tasks and to save time and costs by automating data movement.
3. Azure Data Lake Storage can be used to support Azure Synapse to provide your business with high-performance, scalable data storage.
4. You can optimise your query performance, so your actionable insights arrive at speed. You can use features built into the Azure Synapse environment such as indexed views, result caching and materialised views to refine your performance, and the built-in performance optimisation tools will help you to remove any potential data bottlenecks.
5. Use machine learning and AI because ultimately, they are fast, efficient and introduce layers of automation that reduce the burden while increasing the output. Azure Machine Learning is easily integrated into Azure Synapse so you can build, train and deploy machine learning models on your data. The platform includes pre-built models so you can speed up deployment and results.
An industry-relevant approach
When you lean on the Azure architecture to pull through the data and insights at scale, you see immediate benefits across performance, operations, visibility, innovation and productivity. And these benefits aren’t just felt by enterprises. Companies of all sizes across all sectors can benefit from digging deep within the potential of their data.
Retail can use Azure Synapse Analytics to delve into customer data and enhance personalisation across marketing and engagement strategies. Financial services institutions can use the data to uncover fraudulent activities, ensure compliance and manage large volumes of data at speed. In healthcare, access to patient data is transformed, improving outcomes and physician patient care.
Mint can help you reimagine your data, bringing you all the benefits of data at scale within a proven architecture that can be customised to meet your needs.
