Using big data to stand apart from the competition

Lindsay James
Lindsay James
By Lindsay James on 05 October 2015
Using big data to stand apart from the competition

This article first appeared in the Autumn 2015 issue of OnWindows magazine.

The world has changed. Today there are more devices on the planet than there are people – and these devices create more data than people can consume.

“With the explosion of websites, mobile applications, internet of things (IoT) and cloud-based services that we use at work, home and play, there are vast stores of valuable new data that are being generated,” says Joseph Sirosh, corporate vice president for machine learning at Microsoft.

And it’s not just the volume of data that has amplified – the velocity and variety of data has intensified too. “Data is constantly streaming in,” Sirosh explains. “And there is an increasing number of data types – tweets, web logs, social networks, images, video, GPS and sensor data – that enterprises want to analyse.”

This massive volume of data – known as ‘big data’ – has the potential to give enterprises the edge they need to stay one step ahead. “Half a century ago, the life expectancy of a firm in the Fortune 500 was around 75 years. Now it’s less than 15 years and declining even further,” Sirosh says. “In such a hypercompetitive environment, the use of data and analytics is critical to gain competitive advantages and to be able to react to the trends in the external environment. In many ways, data is the new oil – it can be mined, refined, distributed and transformed into the horsepower to drive a faster, better business.”

Despite this potential, however, relatively few organisations have mastered the art of using big data effectively. According to Dell’s Global Technology Adoption Index, while 61% of global respondents said they had big data that could be analysed, only 39% understood how to extract value from big data and are pursuing it.

“As well as concerns about security and governance, many enterprises struggle with the identification of return on investment, or where to start – from the infrastructure to use, or the tools to employ or the projects to apply,” explains David Leibowitz, director of business intelligence, analytics and big data at Dell. “And if this technology is a paradigm shift from their core capabilities, that can lead to an increase in the costs associated with skills building, managing and maintaining the solution. Also, many solutions assume that one needs to bring the data to the analytics – meaning, you need to transport the data to the tool used to extract insight via querying or advanced analytics. But there’s a new shift – and that’s keeping the data in the form in which it was born, and bringing the analytics to it. That’s sometimes easier said than done, if the data resides on-premises, in the cloud and in a variety of formats.”

Steve Palmer, senior vice president for data and analytics at Avanade, agrees that managing and analysing data is challenging.  “Many organisations are discovering new information, but they’re killing it by applying old-school principles to it,” he says. “They have to accept this new world where there are many different types of data – each of which has a different shelf life and different rules surrounding it. Take social media data, for example. This will have a much shorter shelf life than traditional data. But the rules protecting it are not as strict as those regarding banking activity. These differences create real confusion for many organisations which, while dabbling with data management tools, are not quite getting it right.”

For businesses to make progress, they need to overcome three key challenges. “They need to be able to create a data culture where employees access and use data to inform business decisions; they need to find the right tools to store, process and analyse the massive data volumes and complexity; and they need to build and deploy software applications that embed intelligence derived from all this vast data,” Sirosh says.

Microsoft’s approach is to make it easier for customers to work with data of any type and size – using the tools, languages and frameworks they want to – in a trusted cloud, hybrid or on-premise environment. “Our goal is to make big data technology simpler and more accessible to the greatest number of people possible: big data professionals, data scientists and app developers; but also everyday business people and mainstream IT managers,” Sirosh explains.

While data is pervasive, actionable intelligence from data is elusive. With this in mind, Microsoft has recently launched its Cortana Analytics Suite. “Our customers want to transform data into intelligent action and reinvent their business processes,” says Takeshi Numoto, Microsoft’s corporate vice president of cloud and enterprise, in a recent blog post. “To do this they need to more easily analyse massive amounts of data so that they can move from seeing ‘what happened’ and understanding ‘why it happened’ to predicting ‘what will happen’ and ultimately, knowing ‘what should I do’. Only then can they create the intelligent enterprise.”

The Cortana Analytics Suite brings about this vision by delivering big data and advanced analytics capabilities to help enterprises transform their data into intelligent action. “With Cortana Analytics, we are taking years of research and innovation – spanning technology and infrastructure for advanced analytics, including capabilities like machine learning, big data storage and processing in the cloud as well as perceptual intelligence such as vision, face and speech recognition, with the goal of helping enterprise customers make better, faster decisions to accelerate their speed of business,” Numoto says. “Additionally, the Cortana Analytics Suite integrates with Cortana, Microsoft’s digital personal assistant. Cortana works with the Cortana Analytics Suite to enable businesses to get things done in more helpful, proactive, and natural ways.”

The Cortana Analytics Suite includes Power BI, a service (also available separately) which Microsoft believes ‘will fundamentally transform the business of business intelligence (BI)’. “In the past, BI solutions started with the installation and maintenance of servers and software,” explains James Phillips, Microsoft’s corporate vice president for the business intelligence products group. “Business data was locked up in applications and database systems controlled by IT, so any solution had to start with them. This is changing. Increasingly, and I would argue inevitably, business data is contained in software-as-a-service (SaaS) offerings – Microsoft Dynamics, Salesforce, ­Workday, Marketo, MailChimp, Google Analytics, Zendesk and countless others that Power BI can connect to. With their login credentials, business users have direct access to this data. The growth of SaaS has itself made it possible to offer business intelligence and analytics software, as a service. We believe Power BI is, by a very wide margin, the most powerful business analytics SaaS. And yet even the most non-technical of business users can sign up in five seconds, and gain insights from their business data in less than five minutes with no assistance from anyone.”

It’s clear that Power BI is headlining Microsoft’s efforts to promote the creation of a true data culture in enterprise businesses. “A data culture is one that encourages curiosity, action and experimentation for everyone,” adds Sirosh. “It brings together employees from across disciplines to create a cultural shift – one that empowers people to do great things because of the data at their fingertips. In a data culture, everyone benefits when more people can ask questions and get answers. Technology like natural language query, self-service insights and visualisation capabilities in Power BI support this shift.”

Leveraging this Microsoft stack, a number of Microsoft partners are delivering blueprints to help customers identify the different ingredients they will need on the big data journey, which may include the hardware, cloud strategy, software platform, partner solutions and third-party offers, and end-to-end services to help customers be successful.

“The solutions we develop are provided as certified reference architectures, or as appliances (such as Microsoft Analytics Platform System by Dell) which provide a jumpstart for customers who don’t want to spend time trying to custom-build their solutions,” says Leibowitz. “With proven architectures and ­industry-leading training and deployment services, customers can focus on the business value of their big data challenges, rather than the infrastructure management. And with partners like Microsoft, we can provide and easily on-ramp to hybrid on-premise and cloud solutions so data can reside where it was born in order to reduce the churn on analysis. This means the answer to the big data challenge is no longer an either/or solution. The solutions driven from blueprints illustrate the harmony of architecture that is necessary across the enterprise.”

Avanade, meanwhile, has combined the power of SQL Server 2014 with its global experience and expertise to help businesses make confident, timely decisions to guide them to success today and into the future. “SQL Server 2014 makes it easier and more cost effective to build high-performance, mission-critical applications, enterprise-ready data assets, and data and analytics solutions,” explains Palmer. “We are fortunate to be very close to Microsoft’s product engineering teams and we collaborate on a number of client implementations. Our modern analytics platform is built on Microsoft technologies from the ground up and can help enterprises leverage data from anywhere – whether it’s social media, the internet of things or transactional data – and then pull it into Microsoft Azure. From here, they can use the entire technology spectrum to get the most from the data – from supply chain modelling through to predictive analytics, Cortana and Power BI. The result is a fantastic user experience – one that our clients are reacting very positively to.”

These platforms will undoubtedly prove invaluable in the years to come. “The landscape is maturing, and I think we will see more tools available to improve the experience of extracting value,” says Leibowitz. “There is still a considerable learning curve for the enterprise that doesn’t have the skills to integrate and extract value from big data. The value of technologies like PolyBase become readily apparent for querying data from Hadoop using syntax that many Microsoft users already know: SQL. We will see more tools and automation like this which put data in the hands of business analysts so they can focus on their business challenges rather than the underlying technology.

“Every prognosticator agrees that the use of big data analytics certainly won’t slow down,” adds Palmer. “People will get better at using new tools – especially when they see how companies like Microsoft are making them available to everyone – not just the IT experts.”

“Looking forward, we believe the real value for organisations will lie in the combination of the cloud and IoT with big data technologies, including machine learning, business intelligence and data storage and processing,” concludes Sirosh. “This combination allows organisations to instrument every aspect of how the business operates and use data to make smarter decisions. To get there, organisations need a comprehensive platform to capture and manage all of their data, transform and analyse that data for new insights, and provide tools which enable users across their organisation to visualise data and make better business decisions. That’s why our approach is to make it easy for customers to work with their data on a platform that both integrates and meets them where they are, in the tools they’re using.”


Feature, Big data

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