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State of Technologies at the end of 2016

2016 is almost hitting its end so we thought it’s time to look back at the biggest trends in tech. This blogpost summarize forecasts of trends in Big Data and Data Analytics presented in Forrester and Gartner Reports. It’ll provide you a clear picture of the evolution of Big Data, predictive analytics, IoT and cloud computing market.

 

 

  • Big Data

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It has been a quiet revolution. What is trendy are the growing scale, sophistication and analytics of data. Nowadays data is not just a back-office, accounts-settling tool anymore and the Data Science is not an isolated concept. It is gaining importance in all business sectors and even within all functions. It’s increasingly used as a real-time decision making tool. Moreover, data from social networks, governments or the companies themselves are being analyzed in real time to improve efficiency. Plus thanks to Deep Learning, analytical tools will progressively become more intelligent, autonomous and intuitive in upcoming years. Their operation will gradually move closer to the way of a human thinking, so the unstructured data, such as emoticons used by online users, will be collected and analyzed more quickly and deeply.

 

  • Self-Service Analytics

We are living in a world which is flooded with data captured from multiple sources such as corporate databases, sensors, IoT and this trend keeps increasing. In front of this rising data, organizations are innovating new tools and ecosystems to be able to translate and capture useful information from this data. One of the biggest challenge for Data Scientists is the focus on Analytics and the real-time analysis to make major decisions. To compensate the lack of qualified specialists, and in order to save time, companies will keep investing in data analysis through the Self-Service Analytics tools. With that being said, we’ll keep seeing apparition of innovative tools and other ecosystems for self-service analytics. Plus social networks will develop their own analytical tools. To remain competitive, Data Analysts will therefore have to increase their efforts and inventiveness.

 

  • Public data sources

In the US, for instant, the aggregated health data is now open to the public through the National Center for Health Statistics of the CDC. Without any long wait, many other countries will most certainly follow the same direction. Consequently, these data can now be freely exploited by companies. Besides health, other areas should also soon open access to their data. These open data will give companies gold opportunity to adapt their products, services for niche markets.

 

  • Internet of things:

Over the past decade, the world has become increasingly hyper-connected. We live in an environment where the Internet and its associated services are accessible and immediate, where people and businesses can communicate with each other instantly, and where machines are equally interconnected with each other. IoT will continue changing everything, including ourselves in upcoming years. It’s not a bold statement, consider the impact it already has had on education, communication, business, science, government, and humanity. Clearly, the Internet is one of the most important and powerful creations in all of human history. IoT represents the next evolution of the Internet, taking a huge leap in its ability to gather, analyse, and distribute data that we have been turning into information, knowledge, and, ultimately, wisdom. The worldwide Internet of Things market spend was worth $591.7 billion in 2014 and will grow $1.3 trillion in 2019 with a compound annual growth rate of 17%.

 

  • Cloud Computing:

Due to high costs of infrastructure and administration, data centers are often one of the first business areas that companies consider switching to a cloud service. So an organization’s decision to move their IT to the cloud is gaining importance. Most organizations are planning to shift select capabilities there, and many already have. The decision is often influenced by technology trends, except cost saving benefit, the cloud data center is much simpler to organize and operate and, because it is simple, it scales well. In other words, the larger you make it, the lower the costs per user are. My personal opinion is that organizations will soon get rid of their traditional data warehouse and invest in their next generation data warehouses which will be placed in cloud.

 

For each business, the convergence of IT is an important part of their sustainable growth. All business have come to realize that an integrated IT industry will enhance the competitiveness and creativity of their economies and fuel the sustainable growth of the global economy. Businesses around the globe have been unveiling their innovative strategies for the IT industry. IT technologies have already brought a dramatic change to our lives and will continue to surprise us. We are convinced that in this new era of hyper connectivity, IT will maintain an economic growth worldwide.

 

Sources:

Magic Quadrant for Business Intelligence and Analytics Platforms

National Center for Health Statistics

State of the Market: Internet of Things 2016

From #BigData to #IoT, The Key Technologies of 2020

“Innovation, by definition, is unpredictable”. A Gartner study predict the impact of new technologies in the professional world. There are 47 main technologies that’ll help companies to industrialize the process of innovation. Here below we’ve resumed the most important and trendy ones.

 

Big Data: 

bigdata

The collection of massive data has become a major issue, especially in an era where governments are increasingly on the lookout for personal information. As we’ve all seen in the strategy of Facebook addition of smileys to the simple “like”, the personal data represents an economic value and holding such data may well be a powerful output for the government. Experts have predicted that in 2020 there’ll be 10 400 billion gigabytes of data that’ll be shared every month on the web. This is why the analysis of massive data is a key technology for companies in competition and these business analysis can be helpful for their business strategy to improve management / client relationship.

 

The sensors: 

sensors

The global sensor market is estimated at 154.4 billion dollars by 2020. This figure is explained because of its multiple use, either for the water management, energy management, the analysis of chemical and microbiological pollutants, inventory control in industries or activities tracers in the health field.

A new market is developing around the sensors: biosensors. The biosensor is an analytical tool consisting of an organic compound that allows the connection between biological material and the transducer, which transform the biochemical signal into quantifiable physical signal. It serves in particular to health, environment, safety and food field. It is estimated that sensor market will reach 2.78 billion dollars in 2020.

 

Autonomous Robot: 

Autonomous Robot

Robotics is considered one of the 9 industrial solutions. From a kitchen blander to a human size robot, robotics certainly has a bright future in the new technologies market. As predicted by many experts, robots will soon replace humans to do repetitive or dangerous tasks. For example, when it will be to visit the disaster site or rescue missions, we will send robots instead. However, there’s still a lot to work on robotics before they can perform to any unexpected situations. This is why investments are growing to make it completely autonomous.

On environmental issues, various robots are set up as Diya One of Partnering Robotics for purifying indoor air or Xamen who unveiled a surveillance drone in 2015 to inspect industrial facilities. Robots like Nao will attend everyday life of the older persons. And other will help in the driving area as Valeo, which takes care of parking.

One of the main issues will be the “Sense and Avoid” or “See and Avoid” so that robots can evolve while adhering to the laws of robotics, on which the European Parliament is currently working. The park of “service robots” will reach $ 20 billion and is estimated at 18 million units by 2020. These include agricultural and logistics robots that will get a significant share in the market.

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Artificial Intelligence: 

artificial-intelligence

Biggest dream of AI is to copy and perform exactly like human intelligence, may be in a much better way. A dream slowly becoming reality … or not. Meanwhile, the current IA operates on 3 stages: perception of the environment, a decision that involves the reasoning and learning and environment-oriented actions.

More and more AI is used within the services but it’s also as key elements in decision making support in medical diagnostics (IBM Watson) or in the financial markets sector (algorithms of high frequency trading (THF)) . Thus, 40% of transactions on the stock markets are generated without human intervention. Some AI are also capable of providing decision support such as VITAL algorithm, the Board of Directors of Deep Knowledge Ventures, which participates in investment decisions by analyzing balance sheets of potentially interesting companies. A BBC Research has estimated the global market for intelligent machines (expert systems, autonomous robots, digital support systems) to $ 15.3 billion in 2019.

 

The 5G Infrastructure: 

the-5g-infrastructure

By 2020, the infrastructure of the 5th generation will replace 4G. Faced with the development of the IoT, M2M and environmentally friendly services, it is essential to go beyond 4G. 5G will ensure the continuity and quality of the user experience anywhere anytime. The main quality of 5G compared to 4G will be speed. “As the IoT revolution gets underway, 5G networks will be able to handle the hundreds of millions of devices and sensors that will join the network” says Roger Entner, expert on 5G wireless networks. With this new infrastructure, it will be possible to quickly respond to the challenge of energy efficiency and ensure connectivity with massive data objects Internet

Currently, the European Commission has set up the 5G Infrastructure Public Private Partnership consortium which aims to support the development of 5G standards and strengthen European industry to successfully transition to 5G. The EU is associated with many countries drivers of mobile, broadband including Japan and South Korea. The latter announced that it would invest $ 1.5 billion to deploy the 5G services. A partnership is also planned with China: China’s Huawei has announced an investment of $ 600 million in the development of 5G. What more we can ask for?

 

Internet of Things: 

iot

According to the Institute of Audiovisual and Telecommunications in Europe (IDATE), in 2020 the Internet of Things will be made of 85% of connected objects, 11% of communicating terminals and 4% will be dedicated to M2M (Machine-to -Machine). The global market for the Internet Of Things will reach 1.525 trillion euros by 2020.

 

All these technologies are game changer and will make our future even brighter. Most of us aren’t well-equipped emotionally and culturally to have this much technology entering into our lives but we’ve to embrace them now before it gets too late!!!

Challenges of #BigData

Behind the name of #BigData is hidden an astronomical amount of data produced anywhere, everywhere at any moment by men and machines to each action they perform together and separately.

This production is exploding because 90% of the available data was created only in the last two years. Big Data today is being analyzed to discover the insights that lead to better decisions and strategic business moves.

 

Big data apps are being used to improve offers, service levels and customer support and many more. The following numbers will certainly show you the economic potential of well-established data: Only 17% of companies haven’t plan at all to launch a Big Data project but over 70% of companies have already made use of Big Data, either by integrating their business or as part of a pilot project process. The Data technologies are maturing to a point in which more and more organizations are prepared to pilot and adopt big data as a core component of the information management and analytics infrastructure. It’s an area of research that is booming but still faces many challenges in leveraging the value that data have to offer.

 

Here are so called “big challenges” of Big Data.

 

Find a language for Big Data:

All sciences, chemistry and mathematics have experienced a tremendous boost by adopting a specific language. Don’t you think we must follow the same path in the area of Big Data and invent an algebraic notation and an adapted programming language to better share and facilitate its analysis?

 

Work on reliable data: 

With the explosion in the volume of available data, the challenge is how to separate the “signal” of “data” and “valuable information”. Unfortunately at this point, a lot of companies have difficulty to identify the right data and determine how to best use it. The fight against “spam data” and data quality is a crucial problem. Companies must think outside of the box and look for revenue models that are very different from the traditional business.

 

Data access: 

Data access and connectivity can be an obstacle. McKinsey survey shows that still a lot of data points aren‘t yet connected today, and companies often do not have the right platforms to manage the data across the enterprise.

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Embedding increasingly complex data: 

If the Big Data was first concerned the “simple” data (tables of numbers, graphs …), the processed data is now more and more complex and varied: images, videos, representations of the physical world and the living world. It is therefore necessary to rethink and reinvent the big data tools and architectures to capture, store and analyze this data diversity.

 

Better integrate time variable: 

The time dimension is also an important challenge for the development of Big Data, both to analyze causalities in the long term than to treat accurate information in real time in a large data flow. Finally, the problem also arises in terms of storage. The volume of created data will exceed the storage capacities and will require careful selection.

 

IT architecture: 

 The technology landscape in the data world is changing extremely fast. Delivering valuable data means collaboration with a strong and innovative technology partner that can help create the right IT architecture that can adapt to changes in the landscape in an efficient manner.

 

Security: 

Last but not the least, we’ve security issue. Keeping such vast lake of date secure is a big challenge itself. But if companies limit data access based on a user’s need, make user authentication for every team and team member accessing the data and make a proper use of encryption on data, we can avoid a lot of problems.

 

The change of scale offered by the technologies of Big Data have generated profound paradigm shifts in scientific, economic and political fields. But it also impacts the human field.

 

Xorlogics cognitive abilities are indeed developed to treat and represent all number of data. Big Data thus puts us to the test to challenge our analytical capabilities and our perception of the world. As we change and grow, the beliefs that are most vital to us is to put the people first, follow excellence, embrace the change and act with integrity to serve the world.We at Xorlogics have exceptional expertise in the domain of Big Data like Hadoop EcoSystem (HDFS), MapReduce, Pig, Spark, Storm HBase, Cassandra, MongoDB, Hive, Sqoop, Thrift, Zookeeper, HUE, Nutch Tika, Kafka.

 

So if you are looking for more information or to gain a better understanding of big data terms, tools and methodologies don’t hesitate to contact our experts in the data field!

Internet of Things, a booming connectivity for Africa

African economic pulse has quickened, infusing the continent with a new commercial technology known as The Internet of Things. This new technology offers many prospects for the continent, and can help solve many problems.
In terms of IT infrastructure, Africa is currently very behind compared to other more developed nations. However, more than half sub-Saharan African population has a mobile phone. Therefore, the Internet of Things is the logical continuation in terms of connectivity for the African continent.

IoT in Africa

A driver for economic growth for Africa:
The Internet of Things is much more than a simple technology. This is a product and services ecosystem, from the simple device to the technology of Cloud. As you might know an efficient connectivity adds real value to businesses. This value provides an exciting prospect for Africa, and could result in significant economic growth. The African IT could also quickly catch up and align with the rest of the world.

 

A booming connectivity: 
The adoption of the Internet of Things in Africa is nothing fancy. According to a McKinsey study, the penetration of internet in Africa will triple by 2025 to exceed 50%. This represents 600 million regular Internet users. The study also predict a strong potential for the Internet of Things in developing countries. By 2020, these countries could represent 40% of the global market value of the IoT.
Currently 15% of the world population lives in Africa. More than half of global population growth between now and 2050 is expected to occur in Africa. Therefore, the deployment of a connected system is essential to this.

 

IoT promises: 
The Internet of Things has the potential to solve many problems on the African continent. Many African countries have already embarked on the IoT adventure. Caregivers in Ethiopia monitor patient health status to adapt and adjust their treatment. Nairobi’s connected Traffic lights helps to regulate traffic. In South Africa, utilities suppliers use connected measuring tools to prevent possible overloads. Wildlife is monitored and maintained through connected DNA analysis applications and satellite imagery. DNA analysis has proved a game changer in wildlife.
The potential of the Internet of Things in Africa is unlimited. As technology advances and integrates daily life of most of citizens, we always expect more from IoT solutions to solve the problems.

 

A solution to the agricultural problems: 
In sub- Saharan Africa, 95% of usable land depend on rain. Therefore, food crops are often minimal, and the risk of famine continues to loom as a threat. With the IoT, wireless sensors can monitor the growth, soil moisture levels and water tanks. Smart vehicles can reduce the required physical labor. Thus, cultures can be more prolific, for a lower cost. According to the United Nations Food and Agriculture Organization, agricultural production needs to increase by 60% to feed the entire population expected to reach nine billion by 2050.
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The sensors on their equipment help farmers to manage their vehicles and tractors, reduces time usage while saving fuel. The information is combined with historical and meteorological data, or data relating to ground conditions.

 

Limiting the effects of natural disasters and epidemics: 
Connected Robots can help limit the effects of natural disasters. Still in development pharse, future robots, connected IoT technologies and control mechanisms as SORMAS of SAP could reduce the impact of epidemics such as Ebola. We all know when the powerful earthquake in March 2011 triggered a tsunami that devastated Japan’s Fukushima-Daiichi nuclear plant and raised radiation to alarming levels, authorities contemplated sending in robots first to inspect the facility, assess the damage and fix problems where possible. Ever since, Defense Advanced Research Projects Agency (DARPA), an agency under the U.S. Department of Defense, has been working to improve the quality of robots. It is now conducting a global competition to design robots that can perform dangerous rescue work after nuclear accidents, earthquakes and tsunamis.

 

Several obstacles:
The future looks bright, but there are still many obstacles to overcome. The implementation cost of the IoT infrastructure is very high, and the investments will likely come from outside. Moreover, the hacking risk is a major threat. In addition, it is imperative to deploy training programs to educate and enable it to exploit the opportunities offered by this new technology.

 

The overall connectivity is essential. For now, many African nations are lagging behind in this area. The lack of infrastructure, however, can be beneficial for Africa. Instead of incremental updates techniques, the continent can directly jump into the wagon of new technologies in a way that is not possible for developed countries.
The Internet of Things happen in Africa, and African companies cannot ignore this novelty. Also, be prepared to face challenges in terms of security, and be able to articulate the return on investment are two key points to enjoy this new boom.

 

Sources:
World Population Prospects
What’s driving Africa’s growth
Lions go digital: The Internet’s transformative potential in Africa

Key strategies of a Big Data project implementation

Focusing on Big Data and analytics to create a real competitive advantage requires a structured and effective approach to collect, clean, correlate and analyze all of the gathered data. To facilitate the task, we’ve gathered three key strategies of this process to ensure the success of your Big Data project implementation.

 

Identify and collect important data for your business: 

 

Above everything in Big Data project, it’s essential to target information to be collected in order to ensure a significant return on investment. Avoid investing in information process which cost can be higher than their potential value.

While benefits are being experienced and are expected from Big Data projects, there are complexities that organizations need to consider. The amount of data organizations have access to is expected to continue to increase. The more data there is in different forms (both structured and unstructured); the more complex processes involved to ensure that analysis of the data is comprehensive, meaningful, and useful.

An innovative approach exists and allows, from a graphical interface, easy to use, integrate data of any kind, transform and manage quality, natively in Hadoop clusters. By overcoming the complexities of programming under Hadoop, IT can respond more quickly and less costly to business demands.

 

Manage data quality: 

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Cleaning data while using or storing it in huge repositories is hardly effective. It is best to complete this step “live”: when transactions are in progress within the systems, for example when a user clicks “OK” on your web site, or an RSS feed notifies you a new message on a blog.

Correlate information from different sources is also essential. For example, you can greatly optimize your marketing actions knowing that “tcook 1968” which visited your website is the same person as “Thomas Cook” that made a credit card payment by phone last month, and visited your physical store by presenting himself as “Thomas Cook”.

Create a data quality Firewall can help you ensure the quality of data, before the gathered data spread to other departments of your company. This firewall will improve business processes, reporting and will optimize the correlation and management analysis of Big Data.

 

Analyze and disseminate information: 

 

Business users are now seeking to free themselves from complex solutions, often imposed by the IT department and poorly adapted to their daily needs. The self-service analysis tools today allow many employees to explore their data, to produce content with high added value, and share it across the organization or beyond it.

This agility, access and manipulation of data, however, must not go against the company’s governance rules. For this reason, it is essential to have a platform with security and a unique repository to handle all of the valuable data chain.

The self-service analysis, through a portal or an application, should not overcome information delivery capabilities to a large number of recipients, regardless of the medium (smartphone, tablet) a schedule or updated in real time.

 

Organizations that do not create Big Data projects in an organized, future-looking way may find that their solutions become more challenging and less appropriate to use over time.

Artificial intelligence and connected objects, trends of the upcoming years?

Artificial intelligence

Artificial intelligence, great topic of the moment? Yet the term dates back to the 1950s! AI is the term used most commonly for Artificial Intelligence. The concept is to develop computer programs that perform tasks that are normally performed by human. The goal is to give machines (robots) ability to seem like they have human intelligence. I’m pretty sure that at this point we all have seen robots doing the grunt work in factories, intelligence driverless cars, and companies are using AL to improve their product and increase sales.

 

Since 2007, Gartner has been predicting key strategic technology trends for the coming years – not an easy task considering the rapid change in the IT market. According to a classification made by Gartner, Artificial Intelligence, Big Data, Cloud Computing, sensors, connected objects, smart machines and modern 3D printing are the key trends of the years 2016-2020. Automation and artificial intelligence figure prominently in the top 10 technology trends of the future presented by Gartner at its conference Symposium / ITxpo 2015.

 

Multiple devices, mobile to electronic devices via the connected devices and sensors are the first big trend mentioned by the research company. More and more devices are becoming connected and “resulting in smarter homes, smarter cars, smarter everything. IoT is leading to a point where “no object will just be an object—it will all be wirelessly connected to something else.

 

 Gartner expects more interaction between these connected devices via different networks in the coming years and beyond (via 4G + 5G technologies). The user experience and virtual environments comes in second position. According to Gartner, this presents a big opportunity and competitive advantage to IT developers and enterprises. 3D printing are third in this ranking, which isn’t yet a mature market, but getting stronger. Thus, global shipments of 3D printers for businesses should show 64% of an average annual growth rate until 2019.

 

Information on the massive data processing era (Big Data), followed by advanced machine learning and deep learning are also on the top 10.

 

“The explosion of data sources and complexity of data classification makes traditional (manual) analysis almost impossible and unprofitable for organizations. With artificial intelligence, the chances of error are almost zero in addition to that greater precision and accuracy is achieved. Plus according to Gartner, in 2018, 20% of all business content and documents will be produced by machines.

 

Gartner have published results of a survey on the topic Big Data, artificial intelligence and the relationship between the two domains. Without further ado, here are the main results:

  • 69% of respondents says that artificial intelligence will improve with the massive use of data
  • 68% think that Big Data will be used very long term by public authorities and businesses
  • 67% believe that the Big Data presents long-term benefits for the health and well-being
  • Finally, 65% approves that they use avatars that are digital assistants who interact with the users in order to save the need of human resources.

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Artificial intelligence can provide unexpected business intelligence for organizations, enhance knowledge on their customers and improve customer interaction with the company, and in some case even replace entire departments as intelligent, learning machines perform tasks until now strictly reserved for humans. Not surprisingly, demand for solutions made possible by artificial intelligence is increasing in the private sector as well as in the public sector. “In every organization, IT experts should explore how to use intelligent agents and these autonomous connected objects to improve the activity” said David Cearley, vice -President and associated Gartner.

 

Source: Webbmedia Group – 2016 Tech Trends

How to succeed your Big Data project?

big data project

Big Data is sweeping the business world, there’s no doubt that data-driven decisions and applications create immense value by utilizing data sources to discover, present and operationalize important business insights.

 

Let’s see the list below how you can implement, manage and succeed your Big Data project.

 

  • The initial objective is important

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If your goal is not clear from the very beginning, you may not only be wasting your time but also money on wrong tools so you can easily penalize your project in terms of time and consumed resources. Keep in mind that your goal isn’t to develop a BIG, FAT database but to be able to collect useful information and analyze it in order to take good decisions for your organization.

Many companies focus on collecting as much data as possible from as many sources as possible. While gathering data is important, the second half of the equation — the “science” part — is too often forgotten. You need to approach your big data efforts from a scientific perspective to gain the most benefit from them. If not, you’re at risk of basing your decisions off of bad models, poor data quality, and erroneous assumptions.

 

  • The concept of uncertainty

One of the most significant developments of Big Data compared to more traditional data is the management of the uncertainty. This does not mean that nothing is planned or the Big Data project is launched without preparation. This means, however – and this is particularly true in marketing – that the Big Data project must take into account this uncertainty from the beginning of its design, and operate on a self-learning model. Again, you must, from the start, create goals that allow you to measure your progress along the way. You’ll also need to take into account what data you need, what existing data you have, and how it all applies to your business objectives.

 

  • Intelligent Big Data

Big Data is not a matter of robots. It’s primarily the result of crossing human intelligence, technology and automation. We all know that collecting information into a data lake is one thing, but finding the business value hidden in heaps of structured and unstructured data is quite another. To have big impact of big data and to deliver phenomenal results to meet expectations, they require new profiles at the intersection of different disciplines: computer science, databases, statistics, artificial intelligence, and last but not least, business knowledge (marketing, finance, logistics, etc.).

 

  • Impact of Big Data on organizations

Big data is becoming an effective basis of competition in pretty much every industry. Not only because of new professions emerged, for which the training is still largely to be create. But also because organizations “craft” of business are strongly rethought. One of the more significant impacts of big data is the organizational change or transformation necessary to support and exploit the big data opportunity. Old roles must be redefined and new roles must be introduced, creating both opportunities and anxiety for individuals and organizations alike.

 

  • Big Data technologies are available

Big Data is not only a buzzword but already available here and now. Many of the technologies used in the Big Data have indeed been invented and popularized by Web giants (Google and Yahoo! are among the pioneers) and are now made available to all who are able to implement them.

 

  • The data is the new oil

The distinction between information system (all processes and organizations between data, their process and archiving) and computer system (hardware and especially software used to process the data) is a classic.

The data is still a largely unknown area by the management of who still consider computer systems like magic formulas capable of transforming the business effortlessly. However, the data is capricious, and it requires a lot of work. It’s growing importance in a society where computerization is presence in all sectors, strength to change the perception of this data by the user. Much remains to be done for this change to be fully realized.

 

  • A Big Data project must be managed differently

Big Data is not only a marketing buzz word to describe existing and new technologies but they have their vocabulary, their professionals, their methods, algorithms, and specific projects approaches. Each Big Data project has its specificities. Beyond the technical approach, it induces specific methodology, an appropriate legal framework and a good measure of social impacts.  Learning will be necessary because Big Data are in constant reconfiguration.

 

What can we learn from Big Data? Certainly first of all we should understand what it is and what its value is because working with data is nothing like it was before. The reality is quite different. Above all, we must get rid of some myths like wishing to analyze everything in Big Data. Similarly, the idea of storing everything in order to “do something someday” is just a waste of time. Companies have never been in a better position to leverage the mountains of data available today to quickly gain insights for real business results.

Big Data, Big Problem?

In order to measure the progress of companies in the exploitation of their customer data, EY surveyed some known European companies. The purpose was to see the difference between the “buzz” generated by the fuzzy concept of big data and the reality of large companies. The results of this survey, conducted among more than 150 European companies, reveal that despite a largely positive perception, the “Big Data” hasn’t really taken place in reality unlike it has to be the case.
Let’s check the list below to know more about these issues that’s coming in the way of companies in order to integrate big data in their strategy.

 

Data collection via traditional channels:

Every businesses and organizations accumulate various type of data, such as financial information related to revenues and expenses, data about their customers, vendors and also about their employees. We’ve noticed that traditional file systems are still used by companies to gather data in order to increase their knowledge, understanding of customers, products and deploy marketing strategies. (Storing data in paper files, folders is a form of traditional system).

 

Unstructured data:

Companies collects huge volume of data and need valuable knowledge extracted from these data to improve their business results, still the survey reveals that 45% of respondents agrees that the data collected isn’t sufficiently exploited and only 27% of companies are equipped to manage and analyze the gathered data from many sources.

 

Analytical skills:

One of the top adoption challenges of big data is obtaining the skills and capabilities to interpret it. EY survey shows that for 70% of respondents, a team of less the 10 employees is dedicated to analyze the gathered data. Only 6% of companies have a staff of more than 50 dedicated people to decode useful information from the data.

 

A lack of data processing tools:

Good thing is that most of these large companies are aware of the progress of these unstructured data. 59% of respondents claim to anticipate an increase in the volume of data reliability within 18 months. At the same time, only 27% of them affirm that they have established internal processes to operate reliable or unstructured data.

 

Analysis of the data still (too) little predictive and real-time oriented:

Only 10% of companies operate their customer data for predictive purposes and 5% of them do it to optimize the technical process or to increase timeliness and increased storage capacities (key elements to exploit growing volumes and ever faster data and information flows).

 

The lack of mainstreaming in project management (Big) data:

39% of the respondents recognize that internal silos remain a drag on the optimal use of customer data. Each business has a habit of using and transforming data from its databases to meet its own goals or business issues, capital data cannot flow in the company, which explains the lack of a unified vision.

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The absence of ROI of Big Data projects:

Only 29% of respondents consider that the Big data is a major milestone and has the potential of big impact on business. As for the establishment of a “Big data Action Plan with concrete actions,” they are only 18% who actually did. Regarding the return on investment in particular, 58% of companies surveyed did not seek to quantify the contribution of solutions to their business performance. Again, the gap is huge between the most mature (77%) and “not mature” (3%).

 

Lack of sponsorship from the managing director:

The lack of ROI measurement, coupled with unfavorable economic conditions explain the caution of most CEO on the subject. The majority of small-medium size companies considered perception of top management as a brake on the optimal use of data within their business, 57% of them, against only 11% for the big size companies.

 

The reluctance to share personal data:

The issue related to data security, in which we can add the protection of privacy is the key to the future of the big data. The study of EY highlights that 70% of consumers are reluctant to share their personal data with companies and 49% say they are less likely to do so in the next five years.

 

Low awareness of safety issues and protection of data:

Among the companies EY surveyed, 30% believe they are not concerned with the protection of privacy issues during the operation of their customer data. 92.3% Companies, identified as the most mature in the Index EY Maturity Data, consider that the issue of protection of privacy is a priority. While for 58.6% of those who have been identified as less mature, don’t care about protection issue.

 

To resume:

Two-thirds of European companies (63%) consider that the big data is a valuable and interesting concept but still too vague, difficult to integrate within companies, in terms of organizational transformation, ROI strategy, management and training skills.

 

Even though big data is the petrol of this century, currently, half of the companies did not even studied any opportunities related to big data. Only 9% of companies surveyed have launched both the big data opportunity to study and put in place a comprehensive strategy to manage their customer data. Half of the respondents acknowledged that the absence of “a clear plan of action that constitutes a road map for the entire company” is an impediment to the optimal use of customer data. 57% of companies consider perception of top management as a brake against 11%.

 

The big data approach can be useful and beneficial for every businesses, but without a solid plan aligned with your business objectives you may miss out an elegant solution with a guaranteed return on investment.

Survey : Big Data and the IoT

Connected objects confront the Big Data to new needs, including the quick processing of multiple data sources from the Internet of Things. These levers of innovations are still at stages of maturity, but they represent a real potential for organizations.

 

The rapid development of the Internet of objects has made the data analytics more challenging due to processing and collecting data via different sensors contained in our connected objects. According to the report from IDC (International Data Corporation), the Big Data market will amount mora than $ 125 billion in between 2016-2019.

 

Future of IT: Big Data and Internet of Things are two sides of same coin and a recent study (January 2016) by Tech Pro search shows that Big data and the connected objects are an important economic growth driver via their collaboration in collection of valuable data. Even if they open the possibility of connecting people or objects more relevant, to provide the right information to the right person at the right time, or to highlight useful information for decision making, survey result demonstrate that large companies are more than twice as likely to integrate Big Data solutions than small businesses.

 

The promise of big data depends on the ability of a company to use a connected device to compile data, both internally and externally. Since Big data is a new source of economic value and innovation, the value of data evolves from initial use to future potential uses with higher added value, (all data are thus considered valuable by definition). Study shows that he cost of the analytical processing of big data is expected to decrease this year, allowing companies to collect valuable data more easily.

 

Topics studied in the survey :

  • Data collection via the Internet of Things related to the market place;
  • Data collection via the Internet of operations related data objects;
  • the budget and the number of employees dedicated to the Internet of Things;
  • data security;
  • the advantages and disadvantages of data collection for the Internet of Things.

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Who uses big data?

The first objective of survey was to assess where big data is in use by determining where implementations took place. The study shows that 29% of companies have deployed big data solution, against 61% who did not.

Implementation of Big Data

 

The size of the business is important, because large firms are much more likely to implement big data than small business. In fact, respondents in companies with 1,000 or more employees have implemented big data almost 1.5 times more than those who did not (49% against 35%), main while only a fifth of smaller companies have implemented big data. Three quarters of these companies haven’t any big data solution.

Big Data by company size

 

The region is also important. People whose business is established in the Asia Pacific region are more likely to have responded that their company had achieved an implementation of big data, 19% more than in Europe, which comes in second place. Conversely, the big data is rare in Central and South America.

Big Data by region

Who uses the Internet of Things?

As big data is associated with the Internet of Things, Pro Tech Research also sought to know who uses IoT to collect data relating to the operations or the market place. Only slightly more than a fifth (21%) of respondents say they use the internet of things and 35% plan to put it near future.

IOT

33% of respondents in companies with 1000 or more employees indicate having no current or planned implementation system of IoT, against 59%, 47% and 46% for other companies (ranked in descending sizes). Like the big data, large companies are more likely to have implemented or plan to establish an IoT system to collect internal and external data.

IoT and Big Data

However, it is interesting to note that unlike the big data, internet objects is less likely to be used not in small companies, but in the medium-sized companies (50-249 employees) and midcap companies (250 to 999 employees). This demonstrates that the Internet of Things is more rooted in small businesses as big data, while the reverse is true in both categories of intermediate size.

 

There’s no doubt that IoT is marked by the development of social networks, partnerships and complex interrelations, enabling the development of industrial processes, improvement in services quality and performance available to individuals and consumers. IoT feeds data and increases its value and volume.

 

To learn more about big data and the Internet of Things, download the full report TechProResearch, “Big Data and IoT: Benefits, Drawbacks, usage trends”.

 

Sources:

Research : Big Data and IoT – Benefits, drawbacks, usage trends

3 things to know about Big Data and Predictive Analytics

Big Data Growth

If you’re like most business owners, you’ve probably tried or already trying to accomplish a lot of things with a reduced team. You’ve already tried or you want to give a try to build a sales or marketing team with few resources and few staff members. At the same time, you have to juggle growing revenue, rising funds and expanding your customer/user database. But, in all this rush, there is one thing you mustn’t forget, which is your data.

 

You use them every day by giving them more or less important, (to be honest I think still now most companies doesn’t care enough about data). Yet, they can have a considerable impact on the success of their business. So what can “Data” help you with?

 

Here are three things you must know about the data and its potential to taking your existing business to the very next level.

 

1. Everyone holds the information (data)

Some leaders thinks that their gathered data isn’t revealing or valuable because their business isn’t big enough to gather valuable data. But they’ve to realize that’s NOT true. Even in small companies, data is EVERYWHERE and you must take them into consideration to survive in this competitive world.

 

Everyone who turns on an electronic device and any activity that can be connected on-line, whether a click, online, downloading a document or white paper, generates a “digital footprint.” In 2010, Google Chairman Eric Schmidt said that five exabytes of data were created every other day! To give you an idea, this is the number of data that has been created between the dawn of civilization and 2003. In 2014, IDC (International Data Corporation) announced that by 2020, the universe digital will double approximately every two years.

 

2. Data can interpret your past

Companies that gives importance on their data typically use to interpret the past so they can better plan their future. For example marketers can see the number of visitors who viewed their website over a month, or the percentage of visitors who clicked on pages before leaving the website. A sales manager can gain visibility and detailed reporting on sales opportunities and sales pipelines via sales CRM app.

 

A hand on your data can be useful to review your past activities, make diagnoses and help to better organize future activities. However, you simply get a view of your past performance. The data can only predict but can’t tell you the guarantee about what will happen in the future.

 

3. Data and predictive analytics

The most advanced organizations are, of course, also concerned by “data” by using it as a predictive technology to anticipate and better plan than their competitor. For them, it’s THE tools that allows them to optimize their actions and future decisions. So basically, predictive analysis can predict future trends and behaviors from the existing data.

 

Take for example these below operations. Predictive analytics can help you determine:

 

    • Who is your top priority customer and with whom you must continue your cooperation,
    • The contacts you need to target for a specific action;
    • How and when prospects are likely to buy from you.

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Prediction tools provide clarity to sales and marketing teams to help them to make decisions. Their activities and actions will, for sure, generate the best results for your business thanks to the help of “predictive intelligence”. Predictive analytics actually deals with extracting information from billions of rows of historical data and use it to predict trends and behavior.

 

The different prediction models are designed to determine the changes or similarities in past purchasing patterns and highlight the most important ideas. For example, you can find:

 

  • Which customers your sales team must contact first;
  • What arguments you must highlight for a specific client;
  • What type of content (white paper or video, for example) and what form of communication (email, phone …) will get the best (potential) customer engagement.

 

I’m sure you’ve understood the importance of, even the tiny data, in this huge big data, as most of our activities leave a digital footprint. The analysis of these data and will help you better understand your past actions (strengths, weaknesses and areas for improvement) and then act on your future actions through predictive analytics.

 

Sources:

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