Delivering analysis-ready data to enterprise

With ever-increasing amounts of data, how do Analysts, CDOs and CTO’s deliver analysis-ready data to the C-suite to help shape business decision making

Data is everywhere. Evolving technologies, the consumer shift to digital and the IoT are just a few examples that demonstrate businesses have a massive opportunity to leverage data. Market research leader IDC suggests that by 2025, there will be a massive 163 zettabytes of data – a dramatic rise from 4.4 zettabytes back in 2013.

Stephen Walsh, Managing Director of Realise UNLIMITED, a London-based boutique analytical consultancy, says that their recent survey demonstrated that 81% of C-suite said that data and analytics are critical to business growth.

Walsh says there has been a sea-change from pre-processed; cleansed and well understood data that can be “packaged up in views, cubes and schemas to be mined through and then sliced and diced via visualisation tools”.

Now, he says, “as the data revolution accelerates, our data repositories have evolved into lakes and ponds with the emphasis on volume and richness rather than ease of interrogation. From a business perspective, this has shifted the ‘insight bottleneck’ from IT.”

Walsh insists that the improved data connectivity, “through the likes of logical data warehouses and the commoditisation of ‘data science’ in a lot of business user applications”, has eased the bottleneck a little.

In his opinion, “general data literacy is improving, but data misuse and mis-interpretation is on the rise. Many businesses are not keeping up. The answer is not a simple one. There is no quick fix. There needs to be more integration between ‘business’ and ‘data’ not just through data literacy programs and data science unicorns but a shift to more business strategy leads with a genuine data remit. Achieving this will be the key challenge for businesses over the next 5 years,” he says.

AI-powered analytics becoming smarter and more accurate

Gareth Hutchins is Director, Solution Architecture, Europe & North America for OpenText, an enterprise information management software with a revenue of over US$3bn.

“The amount of data in the world continues to grow at an incredible rate. This massive increase is both a challenge and an opportunity for businesses. Contained within that data is the insight needed to improve decisions, enhance productivity and drive innovation through big data analytics”, says Hutchins.

According to Hutchins, OpenText is seeing the most growth in AI-powered analytics, which brings “human-like” intelligence to understanding the context in vast amounts of structured and unstructured data. 

It combines advanced analytics capabilities with comprehensive AI features – such as deep learning, machine learning and natural language recognition – to uncover the patterns that are contained in information. The strength of this analytics solution is that it will get smarter and more accurate over time as it continually learns from the interactions it has with data but can also be used to unlock insight for sources of data that were previously much more difficult to analyse.”

Richard Chalk, Founder and Creator of Virtlx, a real time monitoring platform, says that regardless of the sector the business is operating in, there are some data points which should always be brought to the C-Suite’s attention: customer sentiment, service levels, product performance and the general performance of the company. 

“Of course, there are more specific points some businesses will require, and that’s why it’s vital to have a documented plan for data collection and how each department in the business will use the results. The C-Suite might, for instance, be interested in why a specific product isn’t selling and the performance of the team during the buyer’s journey. When deciphering data, it also makes sense to understand how the person you’re presenting to digests data. Artificial Intelligence has also become a powerful way to review data holistically,” comments Chalk. 


A culture of measurement and analysis

CFOs and CEOs crave clear data, and cloud cost data is anything but clear, according to Henrik Nilsson, VP EMEA, of Apptio, who develop enterprise apps designed to assess and communicate the cost of IT services for planning, budgeting and forecasting purposes. 

“Understanding data and refining investments requires a culture of measurement and analysis that many businesses do not yet have”, he says. 

A recent study by Apptio and the Harvard Business Review found that 92% of technology decision-makers view the alignment of tech investment and business goals to be important, yet only 62% of them had confidence in the data they had available.

“Without the right processes in place, leaders risk losing sight of the value of investments and lacking the insights to understand what steps are beneficial to the business in the long term. Forward-thinking IT leaders are therefore focusing on cost allocation before profitability. Understanding who is using (or not using) IT resources and assessing the business value it brings to different stakeholders is key to making decisions on where to alter investment and realise transformation projects,” said Nilsson.

Visualisation holds the key to C-suite buy-in

Mohammad Syed is currently the Chief Data Strategist at global data consultancy Carruthers and Jackson. He suggests that “organisations need to remember that data only has value in the context of a business decision, and data teams must involve the C-suite and business analysts from the very beginning of the journey”.

Syed advises data teams to “start by defining the target state and work backwards to determine the overall solution strategy. If you start with the analytical layer, it is a slick way of putting the business outcomes first, and ensures that each layer of the “data delivery stack” is purposeful, valuable and necessary to the goal.

“Great visualisation is key. Data teams consistently underestimate the importance of visual and design when presenting their ideas and solutions, thinking that the “technical build quality” will sell the product instead of an “emotional appeal”. It's critical to understand colour and space theory in order to drive engagement from business users and c-suite executives,” explains Syed. 

“Business leaders are interested in receiving data from across an organisation that can be easily visualised”, according to John Hill, Founder and CEO at Silico AI, a platform that coordinates data and human knowledge to build powerful simulations of a business.

“What the data is saying is fundamental but the presentation of insights is also critical. This means plugging in other skill sets such as marketing and design. We’ve found that visual simulation models are well placed to give decision makers transparent, interpretable and forward looking insights,” says Hill.

The future is business intelligence (BI) and machine learning (ML)

Niamh O’Brien, Manager of Solution Architecture at SaaS data integration service, Fivetran, says: “It’s clear that for businesses that want to successfully integrate the valuable insights from BI while leveraging the predictive forecasting gleaned from data science, a multi-cloud strategy is the future. Using BI and ML processes simultaneously, business leaders will benefit from a comprehensive view over their data as well as the decision-making paths available to them.

Those that are rearing to start the next phase of their analytics journey, however, must evaluate their data governance strategy first. A common governance framework across clouds will be key to avoiding data duplication and any resulting compliance issues. Companies that take the initiative to invest in robust data pipelines and automation will benefit from a single version of the truth when it comes to data, which in turn will enable them to reach business-critical insight in the shortest time possible – ultimately maximising the value of their data, people and technology investments.”

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