How to bridge the production gap between data and IT

Data scientist has been one of the superstar IT roles of recent years, with the promise of spinning data into gold with the application of AI and machine learning.

Using cutting-edge technology to extract deep insights from reams of business data, data scientists aim to help guide their organisations into a more innovative, efficient and profitable future. But so far, return on investment hasn’t always been what companies might hope.

“One of the biggest mysteries in data science today actually has very little to do with data science: What is that last mile to AI ROI?” says Sivan Metzger, managing director MLOps and governance at DataRobot. “You build your machine learning, you find the data, you get it cleaned up, you build the models, you try 90 different iterations, you make a good and clean one and it’s ready to go. What happens then? Why are we not seeing value at scale from AI?”

Metzger credits these issues to a disconnect between the data team, IT operations and stakeholders on the business side (i.e. the potential consumers of data science insights). Data science and IT operations teams have very different considerations and goals – and machine learning is very different from running software. This disconnect is known as the ‘production gap’, and can prevent AI solutions from being properly executed.

Machine Learning Operations (MLOps) is a combination of processes, best practices and underpinning technologies which seeks to bridge this gap by increasing collaboration and communication between data scientists and operations staff – and ultimately ensuring that AI is properly deployed and can begin to deliver the ROI promised.

To learn more about how MLOps can improve your returns on AI, watch IT Pro and DataRobot’s webinar ‘The Last Mile to AI ROI’, in which Metzger and data scientist Rajiv Shah discuss topics including:

• How to eliminate AI-related risks by adopting MLOps best practices
• The inherent challenges of production model deployment and how to overcome them
• Model-monitoring best practices
• Production lifecycle management and why it matters

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Looking back over the past year, it’s clear that for many organisations, regardless of size or industry, technology was invoked to survive the crisis. Much has been reported about the rapid migration to the cloud and the move to support remote working but according to James Don-Carolis, Managing Director of TrueCue, data, and the value which can be obtained from actionable, business intelligence, often acts as the differentiator between success and failure:

“Economic challenges will still make it problematic for businesses to get a full sense of what lies ahead but in order to traverse the current and post-pandemic landscape, those organisations able to make insight-driven decisions will be far more likely to prosper in the coming months and years.”

In light of this Don-Carolis, outlines three key data and analytics trends that will characterise the most forward-thinking businesses in 2021.

Quantifying the true value of ROI

“The focal point of quantifying ROI is so businesses can prioritise investment, but in reality, it can be quite hard for data and analytics initiatives. This is because some of the impacts are direct, such as time saved by automating repetitive tasks, whereas others are less tangible, for example the impact of making quicker and/or better decisions. However, this should not be a deterrent to quantifying impact, because the thought process required for the quantification can itself give benefit.

“Our opinion is before embarking on any data and analytics initiative, the range of likely benefits and business impacts should be discussed, understood and, to the extent possible, measured and quantified. This will also help the business prioritise different data and analytics initiatives. Our experience tells us investment is often mistakenly focused on the ‘visible’ elements (such as front-end dashboards), rather than the ‘behind the scenes’ elements (such as robust data management). In 2021 and beyond, successful business leaders should have their desired outcomes front and centre of any initiatives, and then build data and analytics initiatives around these to ensure a stronger ROI.”

The rise of the Chief Data Office (CDO)

“The position of the CDO has evolved over time to embrace analytics and help facilitate digital transformation efforts. Today, the role has become much more aligned with strategic business objectives, responsible for a host of initiatives including revenue growth, cost optimisation and mitigating risk. We are also seeing greater requirements for this role in smaller organisations too. Because of this, we expect to see a rise in the ‘decision data’ role.

This is where a team or individual takes responsibility for leveraging the insights extracted through data, before analysing and transforming this insight into actionable information which can be used to aid business decision making.

“Importantly, this role should be separate from IT, Head of IT, or the CIO – with the best CDOs performing a hybrid role. Someone that understands how organisations work, paired with commercial elements of a business and understanding the end to the lifecycle of data and analytical projects.”

A smarter approach to data governance

“Whilst it is imperative data is handled in a safe and secure manner, an overcautious approach can result in data being only made available to a minority of users. Good data governance is about liberating information, so it can be shared in a secure and appropriate manner. Establishing a centralised, curated and governed source of non-sensitive data and a trust-based, risk-aware data-sharing model will become increasingly vital for unlocking the benefits of data analytics. Again, having a strong CDO or dedicated data team is key to preventing a company’s data becoming kept under lock and key.”

James concludes: “There are many benefits to improving data analytics maturity levels, including improved forecasting, generating better actionable insights and heightening your understanding of competitors. To progress in these uncertain times, it is critical business leaders continue to leverage the investments made into data initiatives, in order to facilitate smarter decision making and bring clarity at a time of great uncertainty.”

About TrueCue

TrueCue’s mission is to empower business leaders with truth and certainty from their data. We provide high-impact analytical consultancy underpinned by our cutting-edge technology platform. The TrueCue Platform is a SaaS data warehouse automation solution built for the Azure Cloud. Using an innovative no-code UI, it delivers an enterprise-grade data warehouse in a fraction of the time and cost it would normally take and reduces your reliance on technical IT.

The TrueCue Services team bring expertise in data management, data visualisation, data science and enablement. The result? Solutions that are crafted to deliver genuine business insight, enabling you to focus on what matters most: making good decisions using data you can trust. TrueCue is a Microsoft Gold Partner, Tableau’s-longest standing EMEA Partner, and Alteryx EMEA 2019 Partner of the Year.

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Wipro, a leading global information technology, consulting and business process services company and Moogsoft, a pioneer and leading provider of artificial intelligence for IT operations (AIOps), announced a partnership.

Wipro will leverage Moogsoft’s industry-leading platform to deliver next-generation artificial intelligence for IT operations (AIOps) solutions for its customers.

Moogsoft’s AIOps platform, powered by purpose-built Machine Learning (ML) algorithms, helps IT teams in the real-time detection and remediation of IT incidents across applications, networks and IT infrastructure, ensuring continuous service delivery for customers.

Wipro HOLMES, Wipro’s AI and Automation platform, in partnership with Moogsoft, will provide end-to-end capabilities in AIOps transformation. This partnership will help customers dramatically improve the business availability of IT through unified alert management, root cause analysis, proactive anomaly detection and predictive capabilities.

It will enable Wipro to accelerate its customers’ digital transformation journey, and deliver increased business agility, developer productivity, and improved user experience.

Kiran Desai, Senior Vice President and Global Head, Cloud and Infrastructure Services, Wipro Limited said, “Moogsoft is an industry leader and our key partner in the AIOps solutions space. We have also invested in the company through Wipro Ventures, the strategic investment arm of Wipro Limited.

“Moogsoft’s industry-leading AIOps platform will enable our customers to adopt a more proactive and situation-aware incident management approach. We are confident that this partnership will strengthen our AIOps practice for the managed services provider market.”

Phil Tee, CEO and Founder, Moogsoft said, “Wipro has built an impressive AIOps practice to help global organizations accelerate their digital transformation initiatives, which demand continuous service assurance. The combined might of Moogsoft and Wipro will transform the economics of IT Operations and IT support alike by enabling proactive detection of outages, early warning of relevant alerts, and reduced actionable workloads on IT and DevOps teams.

“The patented capabilities of our AIOps platform, combined with Wipro’s market reach and strong managed services portfolio, will enable customers to become more agile and reduce business risks.”

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