As Big Data technology begins to mature, what is influencing the adoption of data analytics?

Big Data and focused Data Analytics are, without question, helping organisations make better decisions that are more informed; more profitable and more predictive. In the current environment, businesses are increasingly driven to have a digital presence to prosper.

But more data isn’t better data unless you know what to do with it. With access to big data starting to mature, analysing the right data is critical.

Whether you are selling products, attracting new prospects for the sales pipeline or creating brand awareness, information is the essential tool sitting behind your digital presence. Throw in the internet of things (IoT) and the data your phone, car, refrigerator, TV or fit bit yields, the volume starts to add up.

Post Big Data Gold Rush, Where Are We?

The so-called big data ‘gold rush’ has led organisations to invest in technology infrastructure, however many then struggle with the right skill base to derive value from the massive data lakes that accumulate.

If 2015 was all about the ability to capture and process data, 2016 will see many businesses looking to new technology to assist with the data analytics. Machine learning, deep insights and predictive analytics are coming (if not already here), yet according to a recent IDG Enterprise report many still businesses remain behind the curve with less than forty percent of those surveyed would be investing in big data analytics in the short term.

Recent Australian technology recruitment data suggests otherwise, with an eight percent year-on-year rise for such roles relating to digital transformation projects, indicating that organisations need the human component of thinking, learning and interpreting that is sometimes overlooked in Big Data strategy.

Real-time Analytics

Hadoop has given businesses significant access to the types of insights that big data can deliver and has given those businesses that invested early some advantage over those who come late to the party.

For many CIOs, however, it’s not yet delivering the anticipated value. Business is shifting its focus from capturing and managing data to actively using it, meaning that the ability to measure data agility is becoming more important as is the shift to processing the data within data lakes.

The proliferation of devices and data sources has exploded the volume of data so that organisations are seeking better ways to pull actionable insights from data in real time and at speed to facilitate their use.

Some of the methods include pre-processing, filtering, aggregation and enriching data as it is captured, which enables more effective and more valuable querying of data lakes later.

There are significant benefits to investing in these methods as part of data capture and processing, namely that it enables faster access to insights that might linger or be lost inside traditional big data analytics. Data analytics – or data science – has a big role to play in enabling businesses to do that.

What Are We Measuring?

With the volume of data available, it is easy to get lost and not have clarity on the key measures required to make decisions. Aligning data analysis with what business objectives and outcomes are and working out how to measure those outcomes (the analysis) is the first critical step.

There isn’t a one size fits all approach to suit all businesses. Here are some examples of the possible business objectives from the online world as a guide:

  • Ecommerce sites – How many products or services are selling? How effectively are we servicing our customer’s needs? Are we effectively marketing, remarketing and supporting the customer journey?
  • Lead generation sites – Are we engaging and converting potential lead opportunities?
  • Content publishing sites – What are our users interested in, engaging with and sharing?
  • Information or support sites – How easy is it for users to find, access and engage with information as and when they need it?

These are measures of users behaviour within a digital marketing context, however by example, these questions align with greater business goals.

Measuring when, where, how and how often highlights if objectives are being achieved or the gaps where they are not.

It’s Not Just an IT Function

Marketers in retail, utility companies and telecommunications – to name a few – are increasingly looking for the technical skills required for data analytics and more of the talent is being recruited to sit in business units other than IT.

A recent report revealed that nine out of ten marketers are buying software such as web analytics and CRMs from within their own budgets, not from the IT budget. 36% of those purchases are for big data analytics tools to facilitate customer transaction analysis.

Half of those surveyed also suggested they are buying services or technology directly because they want flexibility and have a better understanding of what they need in the context of measuring consumer and business behaviour.

Organisations accumulate large volumes of data from many sources, much of it lacking structure as it is collect in databases, from websites, email, transactional software, devices and other sources. Most of this information is being captured for customer services, marketing, sales and support reasons and the case for the ‘single view’ is challenging organisations to derive meaningful measurement and enable real-time decision-making.

As mentioned above, Australian businesses are already looking for the talent they need to implement data analytics projects to achieve exactly that. One of the key challenges is finding the right skill sets to interpret, evaluate and utilise the insights gained from big data.

As the pace of data generation continues to accelerate, it’s clear that data analysis strategy should factor into the business case of big data and be a key part of the management toolkit, not to mention this year’s change and project budgets.

Big Data is Here to Stay

The insights and information available from Big Data, if correctly aligned with business objectives and outcomes, can be transformational.

Knowing what and how to measure is critical to maximise the benefits. However, project fundamentals remain and planning and setting up a focused program/project with clear ownership and outcomes is vital to ensure you are successful.

As your business on-boards the skills it needs, having the right project sponsors in place alongside good governance can make a considerable difference to outcomes.

We believe that quality thought leadership is worth sharing and encourage you to share with your colleagues. If you’re interested in republishing our content, here’s what’s okay and what’s not okay.

To speak to our team about how we can help your business deliver better projects, please contact us.

About Quay

Quay Consulting
Quay Consulting is a professional services business specialising in the project landscape, transforming strategy into fit-for-purpose delivery. Meet our team ...