Big data: Using insights from analysis to drive improved business performance

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1 Big data: Using insights from analysis to drive improved business performance Big data is the key that will unlock knowledge that you didn t even know you had. Use it to spot emerging opportunities and to counter risks before they become a threat to your organisation. The cloud was built to handle the large volatile workloads demanded by big data analysis. WHY YOU SHOULD READ THIS: Discover how big data analysis can give you insights to gain the edge in the market place Be advised of the steps to take for success Understand why the cloud is ideal for your big data strategy Learn how TelecityGroup s Cloud-IX can provide a secure and reliable connection between you and your cloud service provider

2 THE BUSINESS OPPORTUNITY DEFINING BIG DATA You re used to asking your data warehouse for answers to questions that you know, but are you asking the right questions? By analysing large amounts of data from disparate streams, big data gives you the chance to spot trends in your business that you may have otherwise missed. Written by Aditya Ayyagari, TelecityGroup Alan Weaver, Microsoft Whereas traditional business intelligence tools focus on answering well-defined queries, big data systems look everywhere across your structured and unstructured data sets to find emerging patterns. Big data is the key that will unlock knowledge that you didn t even know you had. Use it to spot emerging opportunities and counter risks before they become a threat to your organisation. In the world of big data, the whole is more than the sum of its parts. One of big data s strengths is the ability to infer valuable information from multiple, disparate data streams including private company data and public data sets. Data from various sources can be combined to create new insights that would not have been available from a single source. Many big data implementations are capable of doing this in real time or near-real time, unlike batch-based traditional business intelligence and data warehousing tools. There are a number of benefits a big data strategy can deliver: Reclaim your data lake Business departments have traditionally hoarded data, whether intentionally or not. Siloed infrastructures have locked up potentially valuable data in departmental applications, where much of its value to an organisation is lost. A big data strategy can unlock this data, creating a lake of information that can be used more effectively. Find patterns and correlations The non-relational structures and algorithms underpinning big data analytics are honed to spot patterns in data that relational processing models would miss. Applying these techniques to historical and current data can reveal useful patterns in everything from customer purchases through to supply chain behaviour that can be turned into actionable information for your business. Predict future trends If enough historical data is available, then big data analytics can be used for predictive modelling. Strong patterns based on empirical data can help companies to forecast what may happen in the future. Machine learning, in which computers learn from past trends, is a critical part of the predictive analytics process. Traditional data warehousing involves mostly structured data from transactional systems. The opportunity around big data is about being able to analyse, mine and synthesise insights from structured and unstructured data. That may come from a variety of sources, including sensors (which are part of the Internet of Things), social media, online fingerprints, or transactional systems. The focus is on integrating with and delivering actionable intelligence back into operational processes. BIG DATA IN BRIEF Opportunities Reclaim hoarded data Spot existing trends Predict new ones Challenges Managing storage Processing data Access to expertise

3 BIG DATA LIFE CYCLE CHALLENGES Real/ Near-real time data streams (several or large) Storage Parallel processing Big data is a big burden on IT departments when implemented entirely in-house. The challenges straddle the technical and the organisational. The well-informed IT department will be aware of the hurdles that they face before starting down this path. Next best action or operations intelligence seeded into customer experience processes STEPS TO SUCCESS Insights generation Managing storage On-site big data projects suffer from a key constraint: storage demands. Even though storage costs are constantly dropping, the amount of storage needed for a big data project can be massive. This can represent a considerable investment for the IT department. Processing data Big data processing is a CPU-intensive process. Existing processing capabilities are unlikely to be enough when implementing a new big data solution, because they break down when designers attempt to scale them too far. Big data is a strategic project, providing both technical and organisational challenges. IT decision makers designing big data projects will not act alone. Instead, they will need the expertise of multiple stakeholders to make their project a success. Here are five key steps to success. 1. Define the business case Big data promises to unlock the hidden value in business data, but it is a high-level strategic tool that can be customised to many needs. To make an effective case, you must align it with business goals. Are C-suite executives prioritising revenue generation, risk reduction, or asset consolidation? Listen to your business managers to understand their goals and align your proposal around those. 2. Collect the data Engage departmental managers help eliminate siloed data assets within the organisation. Work with them to extract it and fold it into a broader collection of data that can be used as part of a big data strategy. Devising incentives for them to share data will be a big part of this step. 3. Classify your assets Big data stores are characteristically diverse. Classify data streams that can be used as part of a big data asset. Are they structured or unstructured? What do they represent? 4. Get security and compliance clearance One of the biggest challenges with big data is compliance. Data sets are owned by different stakeholders, with varying agendas. Who owns this data? Are there any dependencies on other data sets, legally, or otherwise? Be sure that you are cleared to use this data and have covered all potential data privacy concerns. 5. Manage cloud migration To truly realise the potential of big data, your data sets may need to be transferred to the cloud to be processed. Design your cloud-based big data project carefully and plan for the extraction, transformation and loading (ETL) of the data you have sourced. Access to expertise Big data is a science, and the systems and data structures underpinning it are different to traditional relational data processing. Companies implementing it on-site will need experts to handle the setup and configuration of the underlying infrastructure. At the application level, on-site big data projects are typically manipulated using specialist tools that may not be a part of an existing employee skill set. Security Collecting together vast tracts of data into a single logical store presents security challenges. Data must be sufficiency cleaned to avoid personally-identifiable information about individuals from being compromised. ID management and authentication must also be managed expertly enough to avoid unauthorised access to this data. Workload sizing Sizing traditional processing capacity for big data environments can be challenging, as big data processing jobs are likely to wax and wane over time. This can leave companies with significant investments in equipment that sits idle for indeterminate periods. ACCELERATING DIGITAL : USING HYBRID CLOUD RESOURCES TO DELIVER BUSINESS OUTCOMES Watch this TelecityGroup Webinar featuring Gartner for advice on how to get the most from your hybrid cloud solution. WATCH WEBINAR 2015 Gartner, Inc. and/or its affiliates. All rights reserved.

4 HOW THE CLOUD CAN HELP USING CLOUD-IX FOR BIG DATA The cloud was built to handle large, volatile workloads, making it perfectly suited to deal with big data needs. It offers a range of benefits for IT departments. Reducing capital expenditure One of the cloud s biggest benefits is its ability to eliminate risk. The less capital that an IT department has to pile into an ambitious new project, the better. Cloud services provide computing power and storage on tap, reducing the capital expenditure that an implementation team would otherwise incur by buying equipment in-house. Scale out, not up Scaling up processing models only works to a point, whereas scaling out can be more effective. Scaling up works by adding more processors and RAM to an expensive, high-end server. Scaling out works by connecting lots of cheaper servers with fewer processors and less memory. Scaling out creates an infrastructure that can quickly be expanded to handle extremely large big data jobs, but it can be difficult to do in-house, because of the complexity and physical computing capacity required. In a cloud service provider environment, scale-out infrastructures are the status quo. Easily access machine learning Machine-learning technology is one of the most significant features of a big data environment, but it is also one of the most difficult to configure and use, requiring significant expertise on the part of the IT department. In a cloud-based environment, big data as a service can deliver the benefits of machine learning, providing reliable, insightful predictive analytics features, without the burden of learning specialist tools and techniques. The cloud lets companies use the right tool for the right task, rather than grappling with restrictive in-house toolsets. Implemented correctly, big data will become an indispensable form of intelligence for a company. The connection that enables it to move data from its own servers into a cloud-based big data processing environment will become a key asset in its infrastructure. TelecityGroup s Cloud-IX provides a trusted conduit to cloud-based services. Security, first and foremost With Cloud-IX, we made a point of emphasising secure communications. The service encrypts all data passing along its dedicated lines, giving peace of mind that your data will be secured between your servers and those of the cloud provider. Reliable service Cloud-IX is built on enterprise-class MPLS technology, which guarantees a level of performance and allows you to size and manage the flow of big data workloads to and from the cloud. Vendor independence Cloud service providers often have their own unique feature sets and ways of working, which means that one big data hosting solution may be different to another. Cloud-IX provides a connectivity solution to a range of different cloud service companies, and handles much of the configuration behind the scenes, making it relatively easy to connect to different cloud providers as needed. ASSESS YOUR CLOUD STRATEGY Is your cloud strategy on the right path for digital transformation? CONTACT AN EXPERT Request a free cloud strategy consultation with our cloud experts. ASSESS YOUR CLOUD STRATEGY CONTACT AN EXPERT

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