Data analytics — A guide for the head of data and BI

By: Ancoris says
Tag(s): Data
Published: Dec 01, 2021
Data analytics — A guide for the head of data and BI

You're aware of the value of data and the business benefits it can bring. But to maximise what you're able to do with your data and the value you can get from it, you need to:

  1. Improve time to insight  — not just in terms of getting the answers more quickly but also presenting them to users in ways that allow them to understand the implications faster and take better business decisions

  2. Process ever larger, more complex and more time-critical workloads

  3. Be able to apply advanced analytics techniques like MLGuide to modern BI evaluations

Traditional BI solutions are failing today's businesses

Legacy data warehouses and BI solutions are struggling to keep up with business demands, user expectations and ever growing volumes of data.

If you're still running legacy BI systems, you probably find that:

  • The time taken to provision new servers, storage and network resources means your systems can't scale fast enough to keep up with data growth

  • Your ingestion tools aren't able to handle the move towards streaming data or micro batching, so they can't deliver data that's fresh enough or current enough to the business

  • It takes too long to create applications and reports to meet new business needs

  • It's hard to provide the right level of fine-grained access to let teams work effectively while still keeping the business and its data safe

  • The traditional architectures of legacy systems don't scale well when trying to exploit extremely resource-intensive applications such as machine learning and AI

  • The pricing plans for traditional data warehouses can easily result in cost overruns, while licence renewal processes are a hassle

What today's businesses need are modern data analytics platforms that deliver actionable insights to everyone in the business, when and where they need them, at any scale. And that's possible thanks to cloud computing. Today's fully managed, modern, smart data analytics platforms running in the cloud are fast, reliable, scalable, efficient and cost-effective.

Modern data analytics — better for users

Business users will enjoy the benefits of a platform that:

  • Provides them with actionable insights at the same speed as business operations, including analysis of real-time data streams 

  • Comes with tools to create fast and reliable data ingestion pipelines, including for streaming data, so users can be confident that the data they're looking at is current and correct

  • Offers tools that allow business users to quickly and easily create new reports without the need to involve data scientists or the IT team  — while your data scientists have access to tools that enable them to exploit data in advanced ways.

Modern data analytics — better for the IT team

Your IT department will love it too. They'll be working with a platform that:

  • Takes advantage of serverless computing to allow your data analytics applications to seamlessly and automatically scale  — even with intensive applications such as such as machine learning and AI

  • OS fully managed, so there's no need to spend time managing servers and storage or upgrading software

  • Provides reporting through any device that has a web browser, so there's no need to worry about whether users have the right apps or extensions installed

  • Incorporates business continuity measures such as automatic replication and backup of data and automatic and seamless failover to a new server instance if there's a server issue

Modern data analytics — better for the data and BI team

For the data and BI team, adopting a modern data analytics strategy will give you a platform that:

  • Let's you deliver benefits in days, not months — for your first project and for every project after that — because you can start building data pipelines, application logic and visualisations straight away, confident that the compute, storage and network resources you need will be immediately available

  • Offers per-minute pricing, so you only pay for what you use — while knowing that you can spin up new resources in seconds for as long as you need them

  • Gives you access to a wider ecosystem of open-source analytics tools that help you innovate in how you combine data, extract value from it and present it to users

  • Can be easily integrated with other applications, letting you embed relevant insights into existing screens in core business apps

  • Is built on a secure infrastructure that will protect your systems, data and users at any scale, including being able to tightly control the data each person can access and work with, down to the level of individual records or columns

The best part of all? Moving to a smart, modern data analytics platform will significantly lower the TCO of your data and BI efforts compared to a traditional data warehouse handling the same loads — by about 40% over three years, if you move to Google Cloud's smart analytics platform rather than simply shifting a traditional enterprise data warehouse into the cloud.

Working with our data analytics and AI team

Our Data, Analytics and AI practice brings together a highly committed team of experienced data scientists, mathematicians and engineers. We pride ourselves in collaborating with and empowering client teams to deliver leading-edge data analytics and machine learning solutions on the Google Cloud Platform.

We have support from an in-house, award winning application development practice to deliver embedded analytics incorporating beautifully designed UIs. 

If you'd like to find out more about how we can help you build your own modern data and analytics platform, why not take a look at some of our customer stories or browse our resources

Modern data analytics platform - 7 rules for success

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