Published in Data content on January 2021. 8 minute read

How to modernise your data warehouse with Google Cloud

Delivering business insights to users can be challenging. Users always want more than the organisation’s IT systems and budget can provide — and it's easy for both your infrastructure and your budget to be swamped by rapidly rising volumes of data. Simply bringing together data scattered across multiple platforms quickly enough to be useful— and making sure it’s combined correctly when it’s been collected in different ways — comes with its own set of headaches. And security is all too often neglected as the IT team struggles to deliver insights, putting the business at risk.

Limitations of traditional data warehouse

Many of these problems stem from the limitations of traditional data warehouse solutions. They don’t scale fast enough, can’t ingest and process new data quickly enough for it to deliver timely insights, and don’t support advanced analytics such as machine learning.

Security measures to protect data often make it hard to share data appropriately to other parts of the business, preventing teams from working together effectively. And renewing licenses for legacy platform can be a hassle and a constant source of tension between what the business needs and what it can afford.

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Modernising with Cloud computing

Cloud computing is now turning this data warehouse landscape on its head. By moving to a cloud-based solution like Google Cloud’s smart analytics platform, you can:

  • quickly and easily handle growing amounts of data and user demand, with fully managed services that take away IT complexity while seamlessly scaling to match the needs of the business
  • gain real-time insights, with tools that can ingest and analyse streaming data as well as data from batch and near-real-time sources
  • innovate with advanced analytics tools like machine learning and custom visualisations, through tools that can be used by your business analysts, with no need to hire scarce data science and data engineering skills
  • easily access some of the best specialist tools on the market, through open and flexible architectures and an ecosystem of partner solutions 
  • deliver insights securely, with best-in-class security that protects systems, data and users at any scale
  • manage and maximise your budget, with flexible, predictable pricing and a TCO up to half that of a typical on-premise legacy data warehouse.

Why Google BigQuery?

Google BigQuery sits at the heart of Google Cloud’s smart analytics platform. BigQuery is a fully managed and serverless enterprise data warehouse that can scale up to petabytes on demand. It supports real-time insights for streaming and batch data, computed right from within BigQuery itself for lightning-fast reporting, and comes with built-in machine learning tools as well as seamless integration with a broad range of specialist tools.

At every step of the way, it ensures your data is always secure, but available to those who need it, with measures such as encryption, fine-grained data access controls to enforce governance and privacy policies, automatic replication of data across multiple data centres and an uptime SLA of 99.99%.

Expert guidance leads to success

But modernising your data warehouse isn’t just about choosing great technology. You need to be able to implement that technology in a way that reduces the risk, complexity, cost and time involved. 

Again, Google Cloud’s smart analytics platform has you covered, with expert design guidance and implementation support from Google Partners like Ancoris, along with out-of-the-box migration tools and a proven methodology that takes you through three stages:

  • prepare and discover, during which we’ll help you identify and document all your workloads and use cases
  • assess and plan, during which you’ll determine the state of your legacy warehouse and evaluate BigQuery through a high-impact proof-of-concept project that can be delivered quickly, while allowing you to understand your specific governance and privacy issues
  • execute, when you’ll iteratively migrate your data and test and validate your ingestion pipelines

With this approach, we’ve been helping clients like Causeway Technologies and Play Sports Network to modernise their data analytics. To find out more, why not download our white paper on the 7 rules for a successful modern data platform — simply click on the download link below. Or come and talk to the experts in our Data Analytics team about your specific challenges and the opportunities that are open to you.

Modern data analytics platform - 7 rules for success

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