In his latest opinion piece Justin Augat, VP Product Marketing from iland discusses how COVID-19 has accelerated the move from a ‘cloud first’ to a ‘cloud now’ approach for organisations.

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Recent market data from Synergy Research Group via CRN suggests 2019 was a milestone for IT and that for the first time ever, enterprises are spending more money annually on cloud infrastructure services than on data centre hardware and software.  For example, total spend on cloud infrastructure services reached $97 billion, up 38 percent year over year, whereas total spend on data centre hardware and software hit $93 billion in 2019, an increase of only 1 percent compared to 2018.  

This means that many companies that have historically owned, maintained, and managed their own IT operations in their own data centre are now evolving how they support their business operations by transforming their IT to cloud.   

Moreover, the cloud continues to be the foundation upon which most organisations’ digital transformation efforts are built, with more than eight out of ten businesses considering the cloud to be either important or crucial to their digital strategies. 

What are the key reasons underpinning this shift to cloud? Much of it is based on the modern organisation’s need for greater agility and flexibility. There has never been a better example of this demand than demonstrated during this COVID-19 pandemic, as companies have hastily decamped employees to home working.  

Likewise, employees today want the ability to work from anywhere and to collaborate with colleagues as easily as they would in person. Even before COVID-19 led to a new remote workforce springing up almost overnight, a growing number of business leaders understood the importance of flexible working. Globally, 50 percent of employees work outside of their main office headquarters for at least 2.5 days a week, with 85 percent saying that productivity has increased in their business as a result of greater flexibility. In addition, more than 16 percent of companies worldwide now only hire remote teams. The cloud enables this freedom to work remotely. 

However, until recently organisations have historically looked at only new application development and deployment for cloud, taking a ‘cloud first’ approach. But now, accelerated by the demands of the modern workforce combined with the ongoing effects of COVID-19, many are pivoting towards a ‘cloud now’ approach. In the months and years to come we will see more organisations embracing agile working and digital technologies, now they have seen a cloud-enabled workforce in action. 

What do we mean when we talk about ‘cloud now’?  

It means that companies are now looking at cloud for more than just new applications, they are considering cloud for all their applications, including existing ones.  

The reason for this is straightforward: companies are focused on reducing costs and eliminating the dependency on the physical data centre is a logical next step in the continuation of this long-term trend. For as long as customers have been buying technology to support business, they have been using it to reduce costs and speed up time-to-market inside the data centre. Technology capabilities including server and storage virtualisation have improved IT’s ability to respond quickly to lines of business. But, over time, the ability of new technology to further reduce costs and time-to-market is diminishing.  

This is a result of the growing customer demand for more application resources, better performance, and increasing frequency of administrative tasks such as patching various components, and planning for end of life or performance upgrades. Likewise, as mentioned earlier, with a global and increasingly remote workforce needing access to their applications from anywhere, this is also fuelling demand. As businesses have reached this inflexion point of diminishing returns, they have turned their strategy to the cloud as the next frontier of IT efficiency, leaving the data centre firmly behind in pursuit of their ‘cloud now’ strategy. 

But today there are hundreds, if not thousands, of cloud services available to organisations. In many cases, the capabilities of the service, adjusted for cost, are what matter most to the decision makers versus the infrastructure itself. As an example, the underlying infrastructure that supports common business software such as Salesforce, Microsoft Office 365, is rarely scrutinised, as the products are trusted solely based on the brand’s reputation.  

But in the case of organisations moving their existing applications to the cloud for production hosting (IaaS), backup (backup as a service) or Disaster Recovery (DRaaS) the underlying platform must be vetted to ensure the application needs will be met. To do this, organisations must examine the capabilities at the platform level. This is where the technology resources that have been purchased come together to deliver the application performance, security, compliance and connectivity, and more, of the selected service. Ultimately, it is these consumed resources that directly impact the cost of the service.  

In general, the main cloud platform types that are most popular and available to customers at scale are public cloud, private cloud, and bare-metal cloud. They all have their merits and downsides and choosing the right cloud will very much depend on the customer’s requirements, as different aspects of these multitude of cloud products will best meet particular application and organisational needs. 

Ultimately, as more customers embrace the cloud for more of their workloads, the varying requirements of these workloads can lead to trade-offs in cost versus performance, which defeats businesses’ main objectives when moving out of the data centre and into the cloud. As a result, customers need to understand a cloud provider’s overall capabilities early to avoid missed expectations in the future as it is clear that not all IaaS providers are the same.   

So, as organisations embark on their ‘cloud now’ approach, they should undertake due diligence upfront to thoroughly consider their own requirements and what type of cloud IaaS provider will best meet their needs both now and in the years to come. Without a doubt we will see more organisations embracing agile working and digital technologies, now that they’ve witnessed a cloud-enabled workforce in action during COVID-19. 

Coeus Consulting, an award-winning independent IT advisory, today announced new research into the approaches organisations are using to drive value…

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Coeus Consulting, an award-winning independent IT advisory, today announced new research into the approaches organisations are using to drive value from their data. The report – Beyond Technology: How can Organisations drive Sustainable Value from Their Data Investments? – highlights that many organisations are potentially failing to realise the potential value of, or monetise their data, despite 74% acknowledging it as a key priority.

The research found that 80% of the large organisations surveyed, believe accountability for data strategy rests with technology leaders such as IT Directors, CIOs or CTOs. Additionally, only a quarter of organisations currently elect to have a Chief Data Officer, with even less placing accountability with others in the C-suite. Emphasis is being placed on speed (32%), cost (28%), and competition (30%), but less so on more fundamental underlying value, the insights it offers, or decision-makers’ ability to develop new products and services from those learnings.

According to one source, DATAVLT, only one per cent of the data companies collect is currently analysed, and they expect as many as 96% of businesses that exist today to fail in 10 years.

“Many investments in data and analytics have been started from a technology perspective with little alignment to business value or desired outcomes that can be measured against a business strategy. Businesses need a change of mind-set and approach right across the organisation, and the challenge is more than simply collecting data and making it available”, commented Richard Graham, Associate Director, Coeus.

However, the survey did find that 66% of respondents are actively trialling the use of machine learning (ML), artificial intelligence (AI), natural language processing (NLP) and automation capabilities. Yet, only 39% admit to widely using data lakes and warehousing, suggesting that organisations have either not completed these activities or are not placing enough importance on them.

“Being data-driven is an imperative for most organisations and there is a growing trend to incubate and deploy advanced analytics, but organisations need to ensure they have certain fundamental capabilities in place before trying to achieve digital transformation.

There seems to be a motivation to be ‘AI first’, perhaps driven by the perception that most organisations are already ahead in using these capabilities, rather than getting to grips with untapped value in existing data, and how best to make use of it” noted Graham. 

The survey results highlight that there are many obstacles to overcome before companies can begin to see meaningful benefits from the data available through technology-led investments such as AI. Of the top five enterprise data bugbears, the majority are business-related: the scale and complexity of data sets (27%); governance and ownership (24%); the lack of a data operating model (19%); regulatory compliance issues (19%); and difficulty in integrating new technologies.

Organisations are facing tougher regulatory environments and when asked to express their concerns about data regulations, compliance with ethical and moral requirements was the biggest, cited by 49% of respondents. This has obvious implications for data management, analysis, and technology buying decisions, and the potential reputational and financial repercussions.

Sixteen per cent of respondents also stated that a lack of expertise and skills is a major obstacle. Whilst companies are investing in foundational skills, moving skills in-house and introducing new roles, third parties and external contractors play a key role in enabling and supplementing these organisations, and will continue to do so.

When asked where organisations are seeing the biggest benefits from their data initiatives, 43% of respondents said they are in ‘improved customer insights’, while 41% identified an improved ability to take proactive, predictive decisions. Improved reporting’ also scored highly, along with better management of risk and regulatory compliance (37%). However, only 24% cited an increased ability to meet customer needs, with 20% citing a greater ability to spot future business opportunities.

In contrast, just 12% identified attracting new customers as a core motivation – the least favoured option on the list, this is despite the realisation that improved customer insight could be the biggest benefit.

“This is surprising given it’s so important in markets that are becoming hyper-competitive. Nearly every type of business is being disrupted by new players and a lack of customer loyalty, especially on new digital channels. Investing in customer insights and new product development ought to be a high strategic priority alongside consolidating market position”, said Graham.

“Being able to seamlessly integrate data and analytics into standard business and IT operations should be the goal of all organisations, to unlock value in your data and information. Businesses need to create an aligned data and business strategy that positions data as a strategic asset, and prioritises resources to integrate data management and analytics effectively”, Graham concluded.

You can view the full report – How can Organisations drive Sustainable Value from Their Data Investments? here.

Professionals will need to learn data science skills to do their jobs and help their companies thrive in the next…

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Professionals will need to learn data science skills to do their jobs and help their companies thrive in the next decade, say business leaders.

Most managers believe data analytics, automation and AI will be essential for business survival in the coming years yet lack the necessary knowledge that underpins it, according to MHR Analytics research.

“We wanted to explore the levels to which organisations across all sectors are developing their data strategies, as businesses get ready to enter a new decade that promises unprecedented digital acceleration,” said Laura Timms, MHR Analytics Product Strategy Manager.

“Without the crucial component of a good data foundation, it is impossible to implement advanced analytics, automation or AI,” she said. “Despite a widespread appetite for adopting these technologies, the study showed that a better understanding of data strategy basics will be vital for companies to launch the data-driven projects they know they need to compete.”

The Data Decade survey, which polled 500 senior technology and finance managers in large UK organisations, found that:

  • More than half (55%), believe data analytics will be essential for business survival in the next ten years, 53% say automation will be essential, and 42% believe AI will be essential
  • A fifth (21%) of UK companies plan to implement AI yet they do not have a data strategy to support it, suggesting a better understanding will be necessary
  • Skills gaps are delaying AI adoption, with 40% reporting this as a barrier to advanced analytics
  • Data science skills will increase in importance, with 43% of senior professionals saying they will need to learn data science or analytics skills to progress their role in the next five years
  • 43% say their role will become more strategic as traditional tasks become automated, with 91% saying their department will become more efficient due to automation.

“The research results demonstrate the positive aspirations that senior leaders have about data-driven technology, and how it will evolve and advance their roles and keep their organisations competitive in the next decade,” said Timms. “But delivering any AI-based system relies on getting the basics right with every aspect of your data quality, and on taking a step-by-step approach to data maturity.”

In the MHR Analytics report, Advancing with Analytics: Spreadsheets to AI, AI expert Bernard Marr reveals how different organisations are establishing data strategies to underpin their AI aspirations.

For example, Marr explains how Royal Shell is using AI to solve the problem facing the company’s drive to roll out electric vehicle-charging terminals.

Motorists weren’t keen to make the switch to electric vehicles while the number of terminals were so limited and while forecourt operators weren’t offering charging terminals because demand was so low.

A focused data strategy underpinning AI techniques offered a solution to this chicken and egg issue. Royal Shell’s RechargePlus programme uses AI to monitor and predict demand for charging terminals throughout the day. By better understanding customer charging needs, power can be supplied more efficiently – which, in turn, saves motorists money and will potentially encourage more motorists to make the switch to electric cars.

More information about progressing along the data journey is available via the MHR Analytics data maturity quiz.

Ends.

*The survey of 500 UK finance and technology professionals employed by large UK companies was conducted by Censuswide on behalf of MHR Analytics in August 2019.

About MHR Analytics

MHR Analytics is a specialist provider of business intelligence, analytics and financial performance management.

The MHR Analytics team enables businesses to capitalise on the data available to them, to identify opportunities and prepare for the future – whatever stage of the data journey they are on.

With an end-to end-suite of quality solutions from IBM, SAP, Tagetik and Microsoft, MHR Analytics supports customers to go beyond intuition and act based on real evidence.

The growing business has been established for 10 years and has a presence in eight countries and more than 20 different private and public sectors, with a proven track record of over 750 successful implementations. Customers include Admiral Group, Rotherham Metropolitan Borough Council, Edinburgh Napier University and Loughborough University.

mhranalytics.com    

About Bernard Marr

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence and big data.

LinkedIn has ranked Bernard as one of the world’s top five business influencers. He is a frequent contributor to the World Economic Forum and writes a regular column for Forbes

Bernard Marr and MHR Analytics have been in partnership since June 2018, with Bernard holding a keynote presentation at the MHR Analytics Summit.

An uncertain business climate doesn’t have to mean uncertainty in your business, says data analytics expert Laura Timms. Despite complex…

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An uncertain business climate doesn’t have to mean uncertainty in your business, says data analytics expert Laura Timms.

Despite complex challenges on the horizon, the wide availability and adaptability of data analytics means managers can take proactive steps to futureproof their organisations.

As product strategy manager at MHR Analytics, the business intelligence and financial performance management provider, Timms sets out five ways companies can harness data analytics to thrive in tough times and plan confidently for 2020 and beyond:

1.    Reduce unnecessary expenses

A key part of preparing for the future is watching what we spend now.

Deciding where to cut funding can easily be left down to intuition rather than truly understanding key and ‘not so key’ revenue drivers.

In Deloitte’s Analytics Advantage report, revenue generation or cost reduction was reported to be the most valued outcome of using analytics.

How? By aligning budgets and resources, funds can be redeployed to meet critical objectives and lower costs. Taking this approach, we recently helped one of our customers deliver savings which equated to a return on investment of 250%.

Analytics acts as a strategic tool which can be used to give insight into areas such as investment opportunities, financial performance and key financial drivers; to give managers peace of mind that resources are always allocated in the right place at the right time.   

2.    From hindsight to foresight – see and respond to changes in real-time

Organisations that are able to respond to changes quickly are better equipped for success.

As Mckinsey laid out in its five trademarks of agile organisationsTechnology is seamlessly integrated and core to every aspect of the organisation as a means to unlock value and enable quick reactions to business needs.”

To future proof a business, it is necessary to evolve from a “hindsight mentality” that tries to accompany change once it’s already happened; to an approach that identifies and responds to changes as they happen in the moment.

This is where analytics comes in. Business intelligence and analytics technology can provide a real-time view of an organisation so that employees can easily adapt systems to changing business strategies and realities.

With analytics, businesses can provide products and services that meet changing customer requirements, match outputs to available resources, and ultimately make smarter decisions.

3.    Scenario modelling to plan for different possible outcomes

There are two types of organisations: those that are reactive and those that are proactive.

While reactive businesses simply try and diffuse an already burning fire, proactive organisations identify the risk factors involved and question not only what they need to do to prevent the fire, but also whether there are any hidden risks or opportunities accompanying the disaster.

The good news is that even for those who currently fall under the first category, data analytics can easily change this.  

Certain analytics technologies provide scenario planning capabilities, which enable managers to model different potential scenarios and outcomes. This can supercharge the effectiveness of decision-making, as it provides front-row seats to see how different decisions will impact the organisation – all without having to commit to one particular course of action.

When this scenario modelling is “multi-dimensional”, you can see how change in one area of the business will impact on other areas, to ensure the whole business is optimised for success.

Whether it’s a change in legislation, cuts in funding or changes to company structure – managers can plan and prepare in advance and reduce the risk of any nasty surprises.

4.    Free up more time to spend on what matters

Chances are, businesses that are not using analytics to carry out their planning are probably relying solely on spreadsheets.

Think of the number of different spreadsheets in your department alone and think of how many hours are spent in a typical week updating these… the answer is probably “too many.”

While spreadsheets are widely seen as the building blocks of planning, relying on spreadsheets alone is neither a reliable or efficient way of preparing for the future.

Repetitive administration tasks can hold companies back and are not always necessary.

A better approach may be to utilise a ‘planning analytics’ solution to reduce these time-consuming jobs and simplify planning, budgeting and forecasting processes.

This eradicates the need for data input-led roles and allows the costs associated with these positions to be better utilised in higher-value tasks. Not only does this provide financial benefits in terms of ROI, but it also works to the advantage of employees by allowing them to focus on ‘what they’re trained to do’ over routine tasks.

Ultimately, analytics frees up more time to spend on the initiatives that really matter, positioning organisations in the best place to meet objectives.

5.    Full organisational view of planning

Without a holistic picture of the organisation, it’s impossible to safeguard it against future changes.

While localised planning limited to individual departments and teams may be convenient, it doesn’t offer the scale of impact needed for success. To truly prepare for the future, the whole organisation has to be on board.

Another downside of relying on spreadsheets alone to plan is that they’re simply not designed to tell the whole story. With different teams using different spreadsheets, input methods and analysis techniques, and little collaboration between this data, the task of collating and making sense of it isn’t an easy one.

On top of this, manually inputting data into Excel documents leaves room for human error, with various studies even suggesting that almost 9 out of 10 spreadsheets contain errors.

Planning analytics software puts all this sporadic data into one centralised place to give a 360-degree view of an organisation.

Through this, you’ll be able to see and understand your business at a granular level so that you can gain early insight into the health of your organisation and plan with confidence.

To learn more about using analytics to plan for the future, take the data maturity quiz which assesses the stage your organisation is on and outlines the steps to take to create a futureproof organisation.

By Lee Metters, Group Business Development Director, Domino, “Get closer than ever to your customers. So close, in fact, that you…

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By Lee Metters, Group Business Development Director, Domino,

“Get closer than ever to your customers. So close, in fact, that you tell them what they need well before they realise it themselves.” Steve Jobs

Every brand aspires to get close to its customers to understand what makes them tick. Those that succeed invariably deliver better experiences that inspire long-term loyalty. Today, the world’s biggest brands know us so well they’re able to personalise their marketing to match our individual tastes and behaviours. When Netflix recommends you try Better Call Saul, it’s because it knows you binge-watched Breaking Bad. The personal approach works; whether it’s a Netflix notification or a ‘programmatic playlist’ from Spotify, targeted recommendations – informed by deep learning and vast data – hugely influence the content we stream. Steve Jobs was right: successful brands get so close to their customers, they can tell them what they need long before they know they need it. And we all keep coming back.

However, not all brands are as fortunate as the digital disruptors. How do you get close to your customer when your brand isn’t an online service that’s routinely capturing user data? If you’re marketing a physical entity – a food, a toy, a designer handbag or a male grooming kit – how do you even know who your customers are (let alone what they need) when complex supply chains inevitably separate you from your end-user? How can you add brand value when you can’t build a direct relationship with your customer or lay the foundation for long-term engagement? The answer is: you can. In fact, as Lee Metters, Group Business Development Director, Domino, examines, with the advent of simple, affordable technology, you can do it quickly, easily, and cost-effectively. 

New opportunities

A convergence of factors is creating new opportunities for marketers to transform the way they manage their brands through the consumer lifecycle. The availability of personalised barcodes combined with the ability of smartphones to read them, has reinvented consumer behaviours, with shoppers increasingly scanning product barcodes to discover more about the brands they buy. However, until recently, the absence of standardised coding meant that brands needed to create proprietary apps to deliver their value-added features, relying on customers’ willingness to download ‘yet another app’ in a world of app fatigue. The introduction of GS1 Digital Link barcodes, which provide a standards-based structure for barcoding data, has removed this need for product-specific apps. It’s opened up the potential for marketing innovation – such as digitally activated campaigns that can transform a product into an owned media channel – enhancing the brand experience and building stronger connections with customers. This key development has been assisted by the emergence of advanced coding and marking systems that are helping brands include more information on every product, allowing them to personalise customer experiences at speed and scale.

With customer intimacy considered a key driver of commercial success, personalised coding and marking can help brands achieve the Holy Grail of getting closer to their customers. What’s more, it provides a platform for value-added innovation that builds engagement, trust, and long-term brand loyalty. The potential applications are exciting and wide-ranging. 

Internet of Products

Digital innovation is not limited to online brands – practically every product can form part of a connected and accessible online ecosystem. An internet of products. In its simplest form, personalised barcoding can provide a gateway to online content – user manuals, product details, blogs, communities, and customer support – that enhances the brand experience. However, beyond the basics, the opportunities for compelling customer engagement go much further. Leading brands are using QR codes to trigger anything from loyalty schemes and competitions to gamification and immersive brand experiences. Progressive brands are using barcodes to create innovative gifting solutions – allowing customers to record personal video messages to accompany their presents, giving their loved ones a more memorable experience.

The potential for innovation is significant – and the rewards are too. For example, in Germany, Coca-Cola used barcoding on cans and bottles to engage directly with consumers, with a simple scan connecting customers with ‘in the moment’ mobile experiences. The digitally activated campaign allowed Coca-Cola to transform its products into an owned media channel, captivating customers with personalised content, incentives, and competitions that generated unprecedented brand engagement. The campaign has subsequently been rolled out across 28 markets in Europe and North America.

Provenance and authenticity

Serialisation, first introduced to safeguard the medicines supply chain against the plague of counterfeit drugs, is now being widely applied across many industries – allowing brand owners and customers to track and trace products and determine their authenticity. This is a significant value-add in sectors like food, where discerning consumers are increasingly interested in the provenance of produce, and the journey foods make from farm to fork. With carbon footprint and other environmental issues now a key influence on consumer purchases, traceability is a major value-add across most commercial industries. 

The value of data

Barcode innovation undoubtedly provides considerable value for consumers. With research showing that customer experience is the most competitive battleground in consumer markets, qualities such as transparency, social responsibility, and open engagement are all crucial ingredients in a trusted brand experience where personalised barcoding can help. But the value exchange isn’t all one way: marketers benefit too.

Direct link barcodes provide a mechanism to capture a rich seam of real-time data that can help brands understand – and respond to – customers’ needs. Simple information such as user profiles, geo-location, purchase history, dates, and times can be leveraged to build a dynamic picture of individual customers, helping to inform a wide range of services and communications. This data can provide a powerful marketing platform – an organic and automated CRM – to target customers and personalise communications based on identifiable preferences and behaviours. Marketers can understand customers’ buying cycles to trigger timely and relevant alerts. They can upsell products and accessories, nudge customers when warranties expire, or past purchases are getting old and tired. And just like Netflix, they can recommend new products that customers will love – long before they know they need them.

Cracking the code

The emergence of GS1 Direct Link barcodes – and the smart technologies that support them – is transforming the retail experience, helping consumers find out more about the products they buy and bringing brands much closer to customers. As the High Street battles tough economic conditions and the rise of digital disruptors, the successful brands of tomorrow will be those that exploit the creative opportunity of personalised barcoding and deploy advanced coding and marking systems that make the magic happen.

It’s time to crack the code.

By Eltjo Hofstee, Managing Director, Leaseweb UK According to a global Gartner survey of 196 organisations 91% have not yet…

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By Eltjo Hofstee, Managing Director, Leaseweb UK

According to a global Gartner survey of 196 organisations 91% have not yet reached a ‘transformational’ level of maturity in data and analytics, despite it being the number one investment priority for CIOs. And with big data set to solve some of the biggest research challenges around today, this needs to change. It is absolutely vital for businesses to be able to process big data quickly and meaningfully if they are to keep on-track with the rapid growth in data.

Along with all the other contemporary buzzwords, ‘big data’ is increasingly thrown around in business and tech sectors as if everyone truly understands it. But do they really? Big data is the description for very large data sets that can be evaluated and provide insights around trends and patterns to drive better business decision-making. 

That may seem fairly easy to comprehend, and although plenty of information is available about big data technologies, few have actually mastered the knack of using big data to its full potential. A survey from Capgemini found that just 27% of executives described their big data initiatives as ‘successful’. This reinforces the fact that, while many are talking about big data and have ambitions around it, the majority of organisations still have quite a long way to go on their big data journey.

Implementing effective, fast data-processing can ensure your company’s continued success. While this may seem daunting, it actually gives us all the ability to analyse more inventively, even more so considering the large, diverse quantity of data produced by businesses these days.

Additionally, considering the growing dominance and capabilities of cloud computing, now is the perfect time to take a deeper look into ‘big data analytics’ so you, too, can leverage the power of big data to bring a greater competitive edge to your company.

Big data + cloud computing = a perfect match

Data-processing engines and frameworks are vital elements within a data system. While there is no key difference between the definitions of “engines” and “frameworks,” it’s important to define these terms separately — consider engines as the component responsible for operating on data while frameworks are typically a set of components that are designed to do the same.

Although systems designed to handle the data lifecycle are rather complicated, they ultimately share a similar objective: to operate over data with the aim of broadening understanding and surface patterns while gaining insight on complex interactions.

To be able to do all this, however, requires an infrastructure that supports large workloads. This is where cloud comes in. Cloud is considered a beneficial tool by enterprises globally because it has the ability to harness business intelligence (BI) in big data. In addition, the scalability of cloud environments makes it much easier for big data tools and applications, like Cloudera and Hadoop, to function.

Available programming frameworks to find a suitable fit

Several big data tools are available, some of which include:

Hadoop: This Java-based programming framework supports processing and storage of extremely large data sets. This is an open source framework and is part of the Apache project, sponsored by Apache Software Foundation, which works in a distributed computing environment. Hadoop supporting software packages and components can be deployed by organisations in their local data centre.

Apache Spark: Apache Spark isa fast engine used for big data processing that is capable of streaming and supporting SQL, graph processing, and machine learning. Alternatively, Apache Storm is also available as an open-source data processing system.

Cloudera Distributions: This is considered one of the latest open-source technologies available to discover, store, process, model, and serve large amounts of data. Apache Hadoop is considered part of this platform.

Hadoop on CloudStack to Crunch Data Successfully

Hadoop, which is based on Google’s MapReduce and File System technologies, has gained widespread adoption in the industry. This framework is similar to CloudStack and is implemented in Java.

As the first ever cloud platform in the industry to join the Apache Software Foundation, CloudStack has fast become the logical cloud choice for organisations that prefer open-source options for their cloud and big data infrastructure.

The combination of Hadoop and CloudStack is really a great match made in the clouds. Considering the availability of big data tools such as these, working in the cloud to leverage meaningful business intelligence, now is the perfect time to harness the power of big data so that your business can think, and achieve, big.

According to an Accenture study, 79% of enterprise executives agree that companies not embracing big data will lose their competitive…

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According to an Accenture study, 79% of enterprise executives agree that companies not embracing big data will lose their competitive edge, with a further 83% affirming that they have pursued big data projects at some point to stay ahead of the curve. Considering that data creation is on track to grow 10-fold by 2025, it’s crucial for companies to be able to process it more quickly, and meaningfully.

Part of the latest in the stream of buzzwords, “big data” gets thrown around in business and tech circles like everyone truly understands it, but do they really? Big data is the label for extremely large data sets that can be analysed and provide insights around trends and patterns to influence better business decision making. 

That may sound simple enough, and although lots of information is available about big data technologies, few have actually mastered the art of using big data to its full potential. In a survey undertaken by Capgemini, just 27% of executives surveyed described their big data initiatives as ‘successful’, reinforcing that while many are talking about it and ambitions around it, many businesses still have much to learn

Implementing effective, fast data processing can guarantee that your company continues to be successful, and is only growing in importance with the diverse, and large, amounts of data that businesses produce. While this can be seen as daunting, it actually gives us all the ability to analyse more innovatively.

Coupled with the growing dominance and capabilities of cloud computing, now is the perfect time to really take a look into “big data analytics” so you too can recognize how the power of crunching big data is bringing competitive advantage to companies.

Big data and cloud computing – a perfect pair

Data processing engines and frameworks are key components in computing data within a data system. Although there is no key difference in the definition between “engines” and “frameworks,” it’s important to define these terms separately — consider engines as the component responsible for operating on data while frameworks are typically a set of components that are designed to do the same.

Although systems designed to handle the data lifecycle are rather complex, they ultimately share very similar goals — to operate over data in order to broaden understanding and surface patterns while gaining insight on complex interactions.

In order to do all this however, there needs to be infrastructure that supports large workloads – and this is where cloud comes in. Clouds are considered a beneficial tool by enterprises across the world because they have the ability to harness business intelligence (BI) in big data. Also, the scalability of cloud environments makes it much easier for big data tools and applications, like Cloudera and Hadoop, to function.

Programming frameworks available to find the right fit

Several big data tools are available, and some of these include:

Hadoop: This Java-based programming framework supports processing and storage of extremely large sets of data. This is an open source framework and is part of the Apache project, sponsored by Apache Software Foundation, which works in a distributed computing environment. Hadoop supporting software packages and components can be deployed by organizations in their local data centre.

Apache Spark: Apache Spark isa fast engine used for big data processing that is capable of streaming and supporting SQL, graph processing, and machine learning. Alternatively, Apache Storm is also available as an open-source data processing system.

Cloudera Distributions: This is considered one of the latest open-source technologies available to discover, store, process, model, and serve large amounts of data. Apache Hadoop is considered part of this platform.

Hadoop on CloudStack to Crunch Data Effectively

Hadoop, which is modelled after Google’s MapReduce and File System technologies, has gained widespread adoption in the industry. This framework is similar to CloudStack and is implemented in Java.

As the first ever cloud platform in the industry to join the Apache Software Foundation, CloudStack has quickly become the logical cloud choice for organisations that prefer open-source options for their cloud and big data infrastructure.

The combination of Hadoop and CloudStack is truly a brilliant match made in the clouds. Considering the availability of big data tools like these, working in the cloud to leverage meaningful BI, now is really the perfect time to harness the power of big data to truly drive your business forward.

With all of the talk about the importance of analytics for finance professionals, by now you probably understand its significance….

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With all of the talk about the importance of analytics for finance professionals, by now you probably understand its significance.

The million dollar question is: are you actually taking full advantage of it?

In reality, ticking the analytics knowledge box or even having an analytics system in place is just the beginning of the story.

There are many core capabilities that are often left untapped which lead to missed opportunities and many financial professionals only partially fulfilling their potential.         

We’ve put together a list of the top analytics capabilities that are often neglected, but if carried out correctly, can provide a whole new level of insight that can work as a long-term strategic asset.  

1.   Syncing data across the organisation

Having an analytics system isn’t just about optimising financial processes.

To get a full picture of the financial state of your organisation, it’s essential to take a holistic view, and to do this, data from across your organisation must be synced and coordinated.

Often, what rather tends to be the case is that teams across the organisation record and analyse their data using their own individual methods. This ultimately leads to mismatched and inconsistent financial data.  

Analytics can be used to store all of your organisational data in one centralised place. Using a data warehouse, it’s possible to even collaborate business processes in real-time so that you can see how changes in other areas of the organisation will directly impact the financials. 

2.   Understanding key value drivers

Knowing your organisations’ key value drivers is key to financial growth. Unfortunately, many rely on rough estimates to determine what these key drivers are.

For instance, it’s easy to assume that core factors like product pricing have a direct impact on revenue, when in fact, this is nothing more than an assumption until proven otherwise.

If you fall into the above category, analytics can be used to “see what the data says” so that you can base this understanding on facts rather than mere theory.

Having this capability will allow you to work directly with your organisation to employ a smart, data-driven strategy that will significantly increase the chances of realising your goals.

3.   Visibility of cash flow

Cash flow is the lifeblood of your organisation and it’s your job to oversee this.

Understanding exactly what’s going into your organisation, what’s leaving it, and precisely when and how this is happening, is a crucial part of avoiding financial issues later down the line.

Analytics can be used to get a multi-dimensional view of your cash flow – looking not just retrospectively, but in real-time, and even to predict what future cash flow will look like.

Using this information and tools like scenario planning, you can plan and prepare in advance and ensure that cash is constantly being allocated to the right place at the right time.  

4.   Automating financial processes

Are you still relying on manual methods to carry out your financial reporting? If your answer to this question is “yes”, then you’re seriously limiting your potential for growth.

Research shows that 80% of spreadsheets contain errors, and reliance on these manual processes alone leave you at risk of non-compliance, not to mention taking up a good portion of your time.

Instead of relying on manually inputting data into spreadsheets, analytics can be used to automate repetitive, low-value tasks; giving you peace of mind that your financial data is accurate and up to par.

Another added benefit is that by freeing yourself from tedious tasks, you’ll have more time to spend on activities that fully utilise your skills so that you can provide greater value in your everyday role.

5.   Insight into profitability

Analytics can be used to drill-down to understand where profit is being generated and how much, as well as revealing areas of the business that are dwindling.

It helps you to answer questions like: What product generated the most revenue for the business within a given time period? What is each customers’ lifetime value? And which areas of the business need extra support to reach revenue goals?

These insights can be fed back to teams in other areas of the business so that the approach can be refined to promote activity that will increase the profitability of your organisation over time.

6.   Predicting sales in advance

Getting your budgeting and forecasting process to a point where you know your estimates are accurate isn’t an easy task – especially when this is left down to manual observation.

Using historical data and a range of predictive techniques, it’s possible to present sales figures in digestible visualisations so that you can easily forecast and make accurate predictions about what future sales figures may look like.

This also allows you to identify patterns and seasonal trends that may impact your organisations’ sales revenue, so that you can plan ahead and ensure that you have enough budget set aside to prevent any cash flow issues.

Analytics is certainly gaining momentum in the conversation of how to be a more effective finance professional, but many are still in the early days of implementation.

To compete in the ever-changing finance space, it’s important to equip yourself with an understanding of how you can use the latest technologies to increase your personal impact and value.

You can learn more about your own level of analytics capability by taking MHR Analytics’ Data Maturity quiz.

References:

https://www.ey.com/Publication/vwLUAssets/ey-how-can-your-finance-function-benefit-from-data-analytics/$File/ey-how-can-your-finance-function-benefit-from-data-analytics.pdf
https://www.educba.com/financial-analytics/
https://www.forbes.com/sites/bernardmarr/2016/04/07/6-key-financial-analytics-every-manager-should-know/#3b58600c55de
https://www.pwc.com/id/en/publications/Actuarial/data-analytics-financial-services.pdf
https://www.pwc.com/us/en/financial-services/research-institute/assets/pwc-fsi-top-issues-2018.pdf

Bersin by Deloitte, 2017: https://www2.deloitte.com/content/dam/Deloitte/ca/Documents/audit/ca-audit-abm-scotia-high-impact_analytics.pdf