Big data to help drive mobile app market past $100 billion

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2016
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The global market for mobile apps is set to reach the $100 billion mark by 2020 as more developers seek ways of monetising their products – but this will only be possible with the help of effective big data analytics.

Prabhjot Singh, co-founder and president of business intelligence service Pyze, told TechCrunch that even though there are millions of entrepreneurs around the world building apps and offering them to the public via Apple's App Store and Android's Google Play, very few of these are financially successful.

Although the world's leading apps can rake in upwards of a million dollars a day, the vast majority have difficulty generating any revenue, with less than 50 per cent of developers making more than $500 a month.

However, this could be changed through effective use of big data analytics. One major reason for the failure of many apps to monetise at the moment is a lack of data and business intelligence that can help developers improve their decision-making and identify better prospects.

But as the technology for evaluating data and turning it into useful information becomes cheaper and more widely available, this presents a great opportunity for smaller app developers to improve their results.

"Companies that can build big data and analytics pipelines to learn about how their apps are being used and who uses them are in the best position to build a community of 'sticky users' who will continually use their apps," said Mr Singh.

He added these players are better able to link into media outlets and social services such as Facebook and LinkedIn to retarget their users and deliver the most relevant, interesting experience. This is something that could not be achieved by the majority of app developers, who may be made up of just one or two people.

Until now, the problem with mobile analytics has been that the solutions that were available did not scale particularly well to provide developers with the type of answers they needed. The tools struggled to effectively analyse millions of data points and then draw out the key information that could give an insight into user behaviour and desires.

Dickey Singh, co-founder and CEO of Pyze, explained that this problem could be solved by using machine learning tools that can automatically cluster groups of users into segments, making it easier to offer more personalised services.

This can enable developers to better monitor usage habits to identify different patterns of app use. 

"From here, an app can begin to develop personalized messages for given users based upon how they use the app," TechCrunch noted. "Nonprofit and for-profit uses of the app can be identified; this enables app developers to more clearly see who is using their apps in a premium, pay-for mode, and where they should be investing their efforts to further monetise their products."

In a study of 12 companies using such tools conducted by Pyze, customer engagement has increased by an average of 35 per cent, while revenue has gone up by 20 per cent.

Prabhjot Singh noted this can help level playing fields between independent designers and large app companies, while also improving rates of engagement for large enterprises that are not primarily in the app business, but that want to use such tools to improve relationships with customers.

Big data spending ‘to reach $187bn’ by 2019

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2016
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Global spending in big data analytics technologies, including hardware, software and services, is set to grow by more than 50 per cent between 2015 and 2019, with investments increasing from $122 million to $187 million over the forecast period.

This is according to research from International Data Corporation (IDC), which noted that the key driver of this will be services-related opportunities, with IT services generating more than three times the annual revenues of business services. 

Meanwhile, software will be the second largest category, generating more than $55 billion in revenues in 2019. Hardware spending is expected to grow to nearly $28 billion in 2019.

Jessica Goepfert, Program Director, Customer Insights and Analysis, at IDC, said: "There is little question that big data and analytics can have a considerable impact on just about every industry. Its promise speaks to the pressure to improve margins and performance while simultaneously enhancing responsiveness and delighting customers and prospects.

The most forward-thinking organisations will utilise the technology at every level of their company in order to make better, data-driven decisions, she continued.

The sectors that will show the greatest interest in big data analytics in the coming years include discrete manufacturing, which is expected to be responsible for $22.8 billion worth of investment in 2019, banking ($22.1 billion) and process manufacturing ($16.4 billion).

However, telecommunications, retail, professional services and government services will also each generate revenues of more than $10 billion from big data by 2019, while the fastest-growing sectors include utilities and healthcare, illustrating how the technology can impact every part of the economy.

IDC also noted that it is not just large enterprises that are set to increase their big data investments. Although the largest firms will naturally generate the higher revenues for the industry, with some $140 billion of the total being created by firms with more than 500 employees, small and medium businesses will remain a significant contributor. Nearly a quarter of the worldwide revenues will come from companies with fewer than 500 employees. 

More than half of big data revenue will come from the US, following by Western Europe and Asia-Pacific. However, it will be in Latin America and the Middle East and Africa where the fastest growth is seen, as companies from around the world get on board with the technology.

Dan Vesset, group vice-president of Analytics and Information Management at IDC, said: "Organisations able to take advantage of the new generation of business analytics solutions can leverage digital transformation to adapt to disruptive changes and to create competitive differentiation in their markets." 

He added that these enterprises should not just be using the tools to automate existing processes, they need to treat data as they would any other valuable asset, by using "a focused approach to extracting and developing the value and utility of information". 

Many firms still lacking big data strategy

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2016
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Big data continues to be high on the agenda for many businesses, but despite the growing recognition of its importance, a large number of firms still do not have an effective plan in place for making the most of the technology.

This is among the key findings of a new survey conducted by DNV GL – Business Assurance and GFK Eurisko, which polled nearly 1,200 professionals from across Europe, Asia and the Americas. It revealed that many expect big data to play a significant role in future operations, but here is still a long way to go for many enterprises before this can be achieved.

More than three-quarters of respondents (76 per cent) predicted that investments in big data technology will be maintained or increased in the coming years, while two-thirds (65 per cent) are planning for an environment where big data is a key part of their operations.

But even though 52 per cent of professionals agreed that big data presents a clear business opportunity, only 23 per cent have a clear strategy in place for embracing the technology.

DNV GL noted that in order to make big data analytics a success, companies should treat it as a new journey, and make preparations and changes to their existing processes accordingly.

For example, 28 per cent of respondents say they have improved their information management procedures in order to make the adoption of advanced analytics tools as smooth as possible, while 25 per cent have implemented new technologies and methods for handling data.

However, fewer companies have worked on changing their day-to-day activities. Just 16 per cent have made efforts to change the culture or organisation to reflect a more data-driven approach, while 15 per cent have changed their business model.

"Big data is changing the game in a number of industries, representing new opportunities and challenges," said Luca Crisciotti, chief executive of DNV GL – Business Assurance. "I believe that companies that recognise and implement strategies and plans to leverage the information in their data pools have increased opportunities to become more efficient and meet their market and stakeholders better."

The survey found that all companies that have already adopted big data analytics report clear benefits from their efforts. For example, 23 per cent stated they have seen increased efficiency, 16 per cent reported better business decision making and 11 per cent witnessed financial savings. 

Meanwhile, 16 per cent stated their customer experience and engagement has improved as a result of big data, while nine per cent reported better relations with other stakeholders.

However, there are several factors that are still holding many firms back when it comes to adopting big data. Chief among these are a failure to develop an overall strategy and a lack of technical skills, both of which were named as issues by 24 per cent of respondents.

Therefore, getting the right personnel on board will be critical in making big data a success. These individuals need to understand the intricacies of big data analytics technologies, as well as take a leading role in preparing the business for the era of data.

Mr Crisciotti said: "The ability to use data to obtain actionable knowledge and insights is inevitable for companies that want to keep growing and profiting. The data analyst or scientist will be crucial in most organisations in the near future."

Telcos turning to Hadoop to help counter fraud

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May
2016
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Many businesses in the telecommunications sector are turning to Hadoop-based big data analytics solutions in order to tackle fraud, a new survey has found.

Research by Cloudera and Argyle Data noted that fraudulent activities are one of the biggest challenges for the industry, with telcos in the US alone losing around $38 billion a year in revenue to this.

Therefore, any technologies that these enterprises can put in place to help identify suspicious activity and put a stop to it before it becomes a major issue will be hugely valuable, and increasingly, Hadoop is seen as the answer.

Nine out of ten telcos (90 per cent) attending a recent webinar organised by Cloudera and Argyle Data stated they intend to use Hadoop to assist in their fraud prevention strategies.

However, just a third (34 per cent) said they currently have a platform in place for this, which indicates there is still a long way to go for the sector as a whole as they try to identify the best use cases for the technology.

Vijay Raja, solutions marketing manager at Cloudera, noted: "Fraud prevention is a textbook use case for Hadoop-based analytics because the ROI is immediately visible.  Real-time machine learning relies on large amounts of data to detect sophisticated revenue threats."

Platforms that are able to combine real-time analytics, machine learning and graphical visibility tools are essential in countering telecoms fraud. These solutions enable analysts to spot fraud attempts as they happen, which traditional monitoring systems can struggle to achieve.

As today's sophisticated, high volume attacks can cost communication service providers millions of dollars in revenue in a matter of minutes, being able to detect fraud quickly will be essential.

Arshak Navruzyan, vice-president of product management at Argyle Data, said: "Unsupervised machine learning delivers everything telco fraud analysts need to be efficient at and deliver immediate ROI." 

How big data is transforming compliance

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2016
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For companies in many sensitive industries, managing their data in order to meet strict compliance rules can be a major headache. Often, regulators demand they keep large numbers of records on hand, which may be very hard to effectively comb through when needed.

It was noted by the Wall Street Journal that compliance applications vary widely, but often start with the company needing to identify what useful data it has available and then organising it into a useful format.

This is something that has proven difficult in the past, but the advent of big data analytics tools are changing this.

For instance, Lionel Wertz, director of corporate services at nuclear reactor company NuScale Power noted that until recently, his firm had operated a paper-based system, which keeps records for as long as 80 years beyond the lifetime of a reactor.

Now, however, it is moving to a data-driven system that will make it much easier to keep control of this information, which it is legally required to archive. This platform will enable it to  track and organise critical engineering information to be quickly searched and pared down.

“I’ll know how long I’ll keep my record for and when I can destroy it,” Mr Wertz said.

However, while some companies have found big data analytics is able to transform how they manage their compliance activities, many more are still struggling, largely because their systems are not equipped to deal with the large volumes of unstructured data that today’s tools generate.

Bob Rogers, chief data scientist for big data at Intel, told the Journal that while nearly every company is exploring how they can improve the use of data, only around half have the technology to pull in large amounts of unstructured data, and only a quarter can convert this into useful insight.

“Unstructured data by its very nature is an inference, it requires context as well as the data itself,” he said. “Determining what to measure and how to measure it has been a real struggle for compliance leaders.”

Among the most valuable information to these personnel will be consumer data and Internet of Things information, which can help improve their daily operations, as well as meeting compliance requirements.

For example, Bank of Tokyo-Mitsubishi UFJ turned to analytics to ensure it was meeting its obligations under Dodd Frank regulations for financial trading, which require all records and events surrounding a trade to be identified and collated.

However, the bank realised it could use this data to study its activities and look for common characteristics that indicate a good trade. It then used this insight to find out which sales practices were working and which weren’t, and reshaped its sales model accordingly.

In the past, this type of big data analysis would be out of reach of all but the largest companies, due to the amount of information to sift through and the computing power required to do this effectively. Nowadays, however, innovations such as cloud computing can give these capabilities to firms of any size, allowing compliance officers more opportunities than ever to not only improve their own activities, but assist the wider business.

Insurers ‘missing out’ on big data advantages

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2016
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Many companies in the life and property/casualty (P&C) insurance sectors are failing to take full advantage of the potential of advanced big data analytics solutions, according to a new report.

Research conducted by Bain and Company revealed that despite some early successes, much of the industry has yet to scratch the surface of what big data technology is capable of. It found one in three life insurance providers and one in five P&C insurers do not apply big data tools to any business functions.

These businesses will therefore lack critical customer insight that can be used to gain a competitive advantage.

Many insurance firms are aware of this issue and have plans in place to increase their spending on big data over the next three to five years. On average life insurance providers expect this to rise by 24 per cent, while P&C providers foresee a 27 per cent increase.

But even among those businesses that are looking to boost their performance, many initiatives will be narrowly focused on two key functions: sales and marketing, and fraud detection. However, these activities are just a small part of what big data analytics can bring to a company.

"In our work with insurers around the world, discussions tend to centre on data management issues and technology investment decisions," said Henrik Naujoks, head of Bain's Financial Services Practice for Europe, the Middle East and Africa and co-author of the brief. 

He added: "Very few are focused on the more important question of how to derive real, valuable insights from the data in order to inform better, more strategic decisions about their business, their processes and, most importantly, their customers."

Bain highlighted three key areas where effective use of big data can help inform decision-making: customer experience, innovation and underwriting.

When it comes to customer experience, for instance, one life insurance producer used big data to develop an algorithm that could identify which prospects could be approved for coverage without the need for an expensive blood test that was previously a standard requirement. As a result, this meant around 30 per cent of applicants did not have to have the test.

Elsewhere, one P&C firm found that underwriting due diligence activities could take up to nine months. But by deploying big data to analyse its own client database, and compare to US federal data on safety violations in order to screen potential clients, it has been able to greatly cut down on the number of site inspections by its engineers, which are both expensive and time-consuming.

This use of big data can also help insurers avoid taking on a high-risk client that could lead to a big payout further down the line.

However, insurers, much like any other business, must recognise that simply investing in analytics solutions alone will not be enough to guarantee success. Instead, analytics must break out of the IT department and be viewed as a key part of the wider business.

Lori Sherer, co-author of the brief and leader of Bain's Advanced Analytics Practice, said: "The most successful insurers break out of the silo and involve business stakeholders across the organisation to inform the analytic development process. The result is insights that are more likely to be adopted by the front line, thereby giving them a competitive leg up in the industry."

7 Social Media Platforms To Build Brand Image For Businesses

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May
2016
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Few years ago, small businesses were in dilemma and had doubts whether social media was worth investing into. But now, it is no longer a question or issue on whether you need to be using social media. Rather, you have to think about the ways on using it effectively and efficiently in order to drive the business forward. A recent statistic was published by iDigic, Social media services for business – a Factosocial 101 infographic. It provides a clear description on how the various social media sites influence the brand value and business of a firm. Sometimes small businesses might feel that social media presence is a kind of luxury rather than some kind of necessity. Social media can be a huge boon for small business and the time they invest will definitely pay off.

Impact of Social Media Worldwide

Do you know there are more than 523,000,000 global users present in social media platforms?

Social Media 101 For Business - Factosocial

Article and Infographic supplied by iDigic

The amount of engagement and followers social media websites like Facebook, Twitter, Instagram and Pinterest brings is humongous. Even for business, social media is a tool by which they can predict the customer requirements and ensure that it reaches to them just like how they want.

Let’s check out how full fledge social media is in achieving the goals of business –

Facebook

Regarded as one of the relevant social media sites, Facebook steamrolls through competition and the clear proof for that is the 1.62 billion users. And the count keeps increasing each day. Like most of the things that are famous, Facebook has immense potential for your business as well as its marketing needs. Statistics show that about 42% of the business feel and accept that Facebook is important for their business. Start-ups can post details of their firm, their stories, and the various products and services that they sell. They can add friends and ensure that to get likes for each post that they submit. There is a likelihood that about 51% of the customers who like your page might be converted into a customer. On an average, individuals spend about one hour everyday on Facebook.

Twitter

Similar to the Facebook, this 140 character limit brings in great leverage to businesses through social interaction. Having more than 320 million users from all around the world this is the perfect for business to increase their engagement rate. Many experts feel that this is one of the most powerful tools for creating a target audience and even it is easy to develop trust and engage with them. Do you know that Twitter provides 21% more engagement rate when there are two hashtags? Twitter is the best hub for women as about 55% of the users in Twitter are women and the remaining ones are males. That is why Twitter is filled with various posts related to fashion and cuisine.

Instagram

It is surprising to know that about 93% of the world famous brands are using Instagram. Basically, this is one of the best social media platform for sharing vivid images with your friends via an uncluttered and clean interface. No doubt, Instagram has become one of the most famous social networking sites to create brands.

Just like other social media sites, Instagram provides business the chance to interact with their potential clients as well as ensure that they make the purchase. There are various studies which show that about 68% of the Instagram users engage with popular brands each day. Even social media marketers like to use Instagram in order to publicize the products and services of their customers.

Pinterest

If you are on the lookout of a social media site which depends on visual content, then Pinterest is the perfect choice which plays second fiddle to Instagram. Also, like the Twitter, this is the perfect for those businesses with deal with products related to fashion and cuisine. So, it is not surprising to see that 79% of Pinterest users are female while the remaining ones are male.

Compared to Facebook, Pinterest generates 27% more revenue from clicks and about 32% of individuals like to surf and pin pictures on Pinterest rather than watch TV. In fact, there are various brands online which use Pinterest to create a solid base to provide easy interactions.

Linkedin

When it comes to professional social network, Linkedin has the biggest followers in terms of working professionals beyond any doubt. Here about 41% of the people use this for marketing their products and services. Just think of it as a place where individuals from various industries discuss their corporate lifestyle and goals and create a long lasting relationship.

Various firms have a solid strategy which involves using the Linkedin profile in order to enhance their online credibility. Furthermore, 97% of staffing departments use Linkedin for recruitment and hiring activities. On an average, an individual spends about 2 hours on Linkedin

Google+

Another famous social media tool is Google+ where 41% of the users interact with their favorite brands. Even though it was backed by the giants of the Internet themselves, initially it had a very unsure start. Later on the folks at big G pulled their act together and currently the network is growing by leaps and bounds. More than 70% of the top brands are using Google+ to market their products and services. Even 51% of digital marketing professionals are using Google+ as it is interactive as well as easy to use. Various statistics show that Google+ has about 540 million active users and the biggest number of visits each month when compared to other platforms.

YouTube

For a long time, YouTube has been associated with providing free streaming of videos and since the takeover from Google, this has reached new heights. About 43% of new users will purchase a product whose ad they seen on YouTube. Firms even experience 31% increase in traffic using the YouTube ads.

In Summary

Social media is one of the major forces in the scheme of business today. For many businesses it has become quite critical to get their brand online and they consider social media as the first step. However, just by selecting the required social media cannot guarantee you the required success unless you plan out the required steps and strategies using it.

From Kognitio’s perspective all of this social interaction and engagement generates data, lots and lots of data. THe faster you can interact with, and query and analyse this data, the greater the liklihood of a high value interaction or outcome event – ultimately what your business wants! So if your analytics can’t keep up or are not fast enough to get that rapid turn-around for an immediate outcome – come talk to us.

White House warns on big data risks

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2016
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A new report on the big data analytics sector from the White House has warned businesses that they must consider the ethical implications of their deployments and ensure that they are not discriminating against any individuals through their use of data.

The study, titled "Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights" noted that if used correctly, big data can be an invaluable tool in overcoming longstanding biases and revisiting traditional assumptions.

For instance, by stripping out information such as race, national origin, religion, sexual and gender orientation, and disability, big data solutions have the potential to prevent discriminatory harm when it comes to activities such as offering employment, access to finance or admission to universities. However, the report warned that if care is not taken with the implementation of these technologies, they could exacerbate any problems.

One of the big challenges is that despite what many people assume, big data is not necessarily impartial. It can be subject to a range of issues such as imperfect inputs, poor logic and the inherent biases of the programmer.

"Predictors of success can become barriers to entry; careful marketing can be rooted in stereotype. Without deliberate care, these innovations can easily hardwire discrimination, reinforce bias, and mask opportunity," the study stated.

For instance, poorly selected data, incomplete or outdated details and unintentional historical biases could all result in the wrong data being input into big data systems. Meanwhile, poorly-designed algorithms can also cause problems if they assume correlation equals causation, or if personalised recommendations use too narrow a criteria to infer a user's true preferences.

The report highlighted several case studies that illustrate how big data can be used to improve outcomes – as well as some of the pitfalls that need to be avoided.

For example, it noted that many people in the US have difficulty gaining access to finance because they have limited or non-existent credit files. This is an issue that particularly affects African-American and Latino individuals, who are nearly twice as likely to be 'credit invisible' than whites.

Big data presents a great opportunity to improve access to credit, as it can draw on many more sources of information in order to build a picture of an applicant. This may range from phone bills, previous addresses and tax records to less conventional sources, such as location data derived from use of cellphones, social media data and even how quickly an individual scrolls through a personal finance website.

However, it warned: "While such a tool might expand access to credit for those underserved by the traditional market, it could also function to reinforce disparities that already exist among those whose social networks are, like them, largely disconnected from everyday lending.

"If poorly implemented, algorithmic systems that utilise new scoring products to connect targeted marketing of credit opportunities with individual credit determinations could produce discriminatory harms." 

The report also included a number of recommendations for improving big data outcomes, such as increasing investments in research, improving training programmes, and developing clear standards for both the public and private sector.

"Big data is here to stay; the question is how it will be used: to advance civil rights and opportunity, or to undermine them," it added.

Enterprises set to boost investment in big data infrastructure

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2016
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Businesses around the world are set to hugely increase their investments in hardware and networking solutions to support big data analytics operations in the coming years, as there is a growing recognition that more robust solutions will be required in order to cope with the huge influx of data.

Research by Technavio predicts that between 2015 and 2020, global spending on servers, storage and networking equipment to support big data activities is set to increase at a compound annual growth rate (CAGR) of 33 per cent, reaching $26.95 billion (£18.48 billion) by the end of the forecast period.

The biggest sub-sector within this market will be for storage tools, which is set to grow from $3.99 billion in 2015 to $17.6 billion by 2020. The study noted that big data storage will require a huge amount of data handling capacity. In particular, solutions that offer a high input/output per second rate will be essential in ensuring that big data analytics activities can be conducted quickly and effectively.

Technavio noted the major types of storage used in big data are network-attached storage and clustered network-attached storage. Both of these are particularly useful when it comes to storing large quantities of unstructured data.

Amrita Choudhury, a lead analyst at Technavio for automatic identification systems, added: "Introduction of object storage is a new trend, which is expected to drive the global storage market over the next four years. It is an architecture that considers data as objects and block storage, instead of file hierarchy."

The need for improved big data analytics solutions is also a key driver for the server and networking markets, as many enterprises are focusing on increasing their performance in this area in order to keep pace with their competitors.

There is also a growing realisation that data is now a key factor in determining a company's market value, which is driving the adoption of analytics tools and supporting systems in many countries around the world.

Servers that feature direct attached storage are the most common solutions for companies that are thinking specifically about how their infrastructure can better support data processing activities.

"The servers possess features such as high compute intensity, better virtualisation capabilities, modular design, scaling capacity, highly efficient memory, and processor power utilisation, which make it an inevitable part of big data structure," Ms Choudhury stated. 

Global spending on server solutions for big data is expected to reach $6.6 billion by 2020, while networking tools, including cabling, routers and switches, with grow by 36.49 per cent CAGR to reach $2.75 billion.

What happened to the ‘data gravity’ concept?

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2016
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A few years ago, one of the emerging thoughts in the data storage sector was the idea of 'data gravity' – the concept that the information a business generates has mass that affects the services and applications around it. The more data firms create, the more 'pull' it has on surrounding parts of the organisation.

The term was coined back in 2010 by Dave McCrory. In his original post, he spelled out how as data volumes grow, the effect they have on other parts of the IT environment becomes more pronounced – in much the same way that a larger planet or star exerts a greater gravitational pull than a smaller one.

Back then, when big data was still in its infancy for many companies, there was a great deal of uncertainty about the impact that growing volumes of data would have on a business, and Mr McCrory's concept helped get IT professionals used to the idea of data as having a tangible, real-world impact on how a firm operates.

These days, it's not a term that you hear very often. But why is this? It's not exactly the case that the concept hasn't worked out, but as big data technology has evolved, its rather been overtaken as the accumulation of vast quantities of data becomes the new normal for many firms – the influence has moved from local planet gravity to cosmos 'market' scale gravity.

When Mr McGrory first described the concept, tools like Hadoop were still a long way away, and the impact that the platform has had on the big data market has been huge. As a result, the notion that data has a 'pull' on just parts of the IT department has progressed to an enterprise level influence.

Many strategies are now more guided by ideas such as the 'data lake' – where all of a business' generated information is pooled into a central resource that businesses can dip into whenever they need it. Is this the ultimate evolution of the gravity concept – a data black hole – hopefully one where information escapes!

The idea of data having 'mass' that can affect other parts of the business hasn't gone away – it's just become the accepted truth, the norm, as more companies put data, and the information derived from it, at the heart of their activities.

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