While running a business, one should consider not only internal data but external ones as well. Due to the inability to access information and integrate it, businesses are lagging behind. Though a huge amount of external data is available, it’s not always easy to find the desired information. Certain software aid the process of finding external data. Bringing both external and internal data together provides a unified view as well as helps in the process of decision-making and discovering insights. Data from all sources should be brought together and technologies that are able to perform this task and are able to put equal importance to all sources of data should only be accepted. Read more at:https://channels.theinnovationenterprise.com/articles/does-your-car-have-more-awareness-than-your-business

Nowadays, like other fields, big data insights affects strategies of digital marketers helping them to create effective campaigns. The discovery of various marketing technologies makes it clear that, companies are keen to invest in this. Sentiment Analysis tool is unethical but not illegal and is really helpful to find opinion –rich information to be acted upon. This “opinion mining” with the help of other tools can actually manage conversations about a brand when used with some other tools. But the drawback of it is we never know if the analysis becomes misleading and leads to the loss of a brand. There are many more such tools used. This proves the relationship between big data and digital marking has transformed into a more sophisticated one. Read more at:  https://channels.theinnovationenterprise.com/articles/where-big-data-marketing-meet

The present events ongoing in the world economy give us the impression that we are amidst turbulence and chaos. To become more active and adjust to rapidly changing events, Finance Planning and Analysis (FP&A) departments should consider a vast amount more of data for forecasting. A lot of this can be achieved by making use of advanced technologies like Cloud, Big data and analytics. With Cloud, necessary information can be disseminated to required destinations. FP&A organizations are now moving from spreadsheets to enabling technologies and integrated platforms thus ensuring transparency of assumptions and drivers. Big data and analytics enables faster than ever processing of data. Using software, sifting through a chunk of unstructured data and identifying patterns has become easier. Read more at: https://channels.theinnovationenterprise.com/articles/the-rise-of-the-rolling-forecast-for-fp-a

Delivering added business value to existing product and services can be done through the Internet of Things (IoT). IoT can help organizations improve relation with customers without much physical interaction. Using IoT, personalized services can be delivered in a less personal way. The key to launching IoT is to think big. Organizations should be able to identify the limitations yet be able to offer integrated services including IoT and other services and applications. After creating an understanding of IoT, companies should communicate its values, potential, risks and ecosystem roadmap implications. An example of how IoT can be used to deliver personalized services can of the car insurer who, in the event of an accident of his customer, is informed immediately through the car's on-board systems. Read more at:https://channels.theinnovationenterprise.com/articles/7726-why-a-customer-is-never-a-thing

Cancer is a disease that had killed many people in past decades. Few years back it was not possible to treat a patient suffering from cancer. Now doctors have treatment of cancer. But it could more easier with the help of big data. Let us see how big data make it easier. 

Doctors collect data from pre and post treatment of patients. Predictive models can be formed using the extensive data that can help doctors to analyze whether a treatment is success or failure for some set of patients. There are some advancements where AI is used in diagnosis and treatment of cancer. With the help of big data analytics doctors can see which drugs are most effective in treatment. Also running analytical models doctors can find which drugs are not necessary and significant. Only necessary drugs can be used to target the specific forms of cancer. The systematic and data driven view for looking at cancer has increased the potential for its prevention. Read more at:https://channels.theinnovationenterprise.com/articles/big-data-in-cancer-revisited

Big data can provide contextual intelligence, which would work as a catalyst in supply chain operations. While legacy ERP (Efficient Resource planning) and SCM (Supply Chain Management) are designed for order, shipment and transactional data, big data can create knowledge sharing supplier networks, revolutionizing the supply chain. Delivery networks can be optimized using geoanalytics, which fixes one of the major challenges in this business. Companies that have adopted big data analytics say that there is improvement in customer service and demand forecasting and optimization of inventory and asset productivity. Read more at: http://www.forbes.com/sites/louiscolumbus/2015/07/13/ten-ways-big-data-is-revolutionizing-supply-chain-management/

To stay ahead of new disruptive competitors, banks must understand the value of the data produced from daily transactions across email, mobile and online channels by digitally-led customers and use them to build on their strengths. High street banks and private financial service organizations give customers potential to develop new initiatives with cross-marketing events, loyalty programs. Bank must adopt a mobile-first strategy which engages with customers to maximize longevity. They must deploy mission-critical analytics tools with access to real-time data. Also, more flexible and intelligent OS harnessing the use of big data must be used. By using sophisticated analytics features, banks’ risk management departments can access information on customer-purchasing behavior enabling them to make immediate adjustments to individual customer credit limits or lending rights. Read more about it at: https://channels.theinnovationenterprise.com/articles/7749-how-is-data-remodelling-the-fs-ecosystem 

A loyalty program is less about points and rewards and while these perks might attract consumers, they don’t suggest a sense of loyalty. In this age of data, the focus of these programs should be collection of useful data to help maintain good relations which benefit both consumers and the brand. However a business that trusts consumer-provided data is a business making decisions based on what is untrustworthy, random information. From observation of customer activities and external data sources, advanced analytics can create a profile of the customer for precise segmentation of the customer base. Business analysts and data scientists agree that expanding the data for any given model will typically produce dramatic improvements in analysis. That’s why many organizations have turned to a Big Data solution. Read more at: http://www.smartdatacollective.com/davemendle/323701/redefining-loyalty-programs-big-data-hadoop

Up to 16 Exabytes of RAM can be supported by a 64-bit system. Machines with 128GB RAM or more are becoming common with this era of Cloud Computing and Big Data. The data sets for Big Data are getting too large for even heavily loaded machines with memory despite the best efforts, don't fit into the RAM even after clustering in some cases. Researchers at MIT created a cluster called BlueDBM using Solid-State Drives (SSDs) to get rid of the memory problem. They also moved some of the computational power off the servers and onto chips. By pre-processing known parts of the data onto the flash drives prior to passing it back to the servers, the chips made distributed computation much more efficient than before. They thus got rid of the overhead of running an operating system. Read more at: http://www.itworld.com/article/2947839/big-data/mit-comes-up-with-a-no-memory-solution-for-big-data.html

Uncontrolled urbanization is posing as a great threat as it puts immense pressure on the resources available. Some of the issues that will be faced in this scenario are clean water, clean air, power, waste management and living space.
Big Data and Internet of Things (IoT) are some of the technological forces which are pushing towards smart cities. With the help of Big Data a range of applications are being made available with the help of which smart cities can be made more livable. Applications like smart street lights are already being used in smart cities like Birmingham. Street lights are attached with sensors which monitor footfall and noise levels and based on this data, the light turns on or off. Cities like Bristol, England are installing an infrastructural network that will support the data generated through Big Data and IoT.
These examples are minor steps in building of Smart cities which can sustain growing population without hampering the quality of life. Read more at: https://icrunchdatanews.com/big-data-building-smart-cities/

There is no doubt about the revolution that big data has brought to the way business is done. But, most of the talk has been around the structured data. It has been increasingly becoming clear that the potential of big data can be truly understood if we take up the challenge of harvesting unstructured data. Jonathan Buckley, senior vice president of marketing at Qubole, in an article in Smartdatacollective emphasizes that if businesses want to remain relevant and profitable then it’s the right time to turn their attention to text analytics. The most important advantage that text analytics have is that it provides with a much larger sample of customer sentiment and extract data which is otherwise not quantifiable. But all of this boils down to having the right technology. For more on this follow the link http://www.smartdatacollective.com/jonathanbuckley/329383/text-analytics-next-frontier-big-data

Going digital has its own advantages. Along with flexibility, adaptability it allows for transparency and openness. With increasing openness and transparency, customers get to know the whole truth which helps them to trust better. Lack of trust is prominent among leading societies and economies nowadays and it has impacted them. Customers trust what they use and this is the whole point of digital transformation. It has its own culture that empowers us with digital tools to know more about the customers. Its span includes the big data surge. With more information on customers focus has been shifted to the effective use of these data. Again, while collecting personal data from customers there is often a lack of trust which hinders the whole process. To know more, please follow: http://www.cmswire.com/digital-experience/digital-change-is-cultural-change/

There are a lot of open source analytics tools available that every user can easily find on websites. But to make appropriate use of such tools each company requires equally compatible skills. So companies are required to invest heavily to develop such skills and also on collecting data. It has been found that companies are spending on an average of $7.4m on data initiatives in 2015. Free platforms also took huge investment such as Hadoop, making more efficient systems. The increasing data size led to increase in expenditure, and is likely to increase in future. Upgrade is required in currently installed systems to process huge data in less time. On the other hand huge investment is required to meet the heavy salaries of data scientists, which is approximately $118,000m. As the supply of qualified data scientists increase this amount will fall, which decreases the overall amount of employee compensation. There is a strong evidence that spending on data initiatives has been increasing at a surprising rate and is likely to continue for next 2 years which ensures a boom for the big data companies.  Read more at:https://channels.theinnovationenterprise.com/articles/big-data-spend-is-increasing

Data science is the most dynamic and multifaceted industry providing useful and interesting insights with the data. Recently due to more than exponential growth of data and digital revolution, it is becoming increasingly difficult for organizations to use this data efficiently. Sifting data has become cumbersome and getting to the right data has become a top priority. Thus most organizations are formulating strategies to use this data wisely without any hassles. From operational procedures to recruiting employees, right data can direct to right ways of doing it. Thus CEOs are showing more interest in this digitized environment. In short an overhaul in usage of data driven techniques are taking shape to have a leading edge. To  read more: http://www.predictiveanalyticsworld.com/patimes/plotting-your-data-science-strategy-0618152/

Dubai Airports CEO, Paul Griffiths, is revolutionizing the airport experience and working. The Dubai Airport is handling 120 million annual passengers. This causes a need for something preventing the degradation of customer experience. Using in-dept. analytics to assign gates in a dynamic way is the first step. The system can assign gates in a far more efficient manner – such that if two flights have a significant numbers of passengers common between them, they will dynamically be assigned gate positions as close as possible. A new initiative allows retail stores in the airport to scan passengers' boarding passes and provide current updated about their departure gate, time, and the estimated time to move from the customer's current position to the gate. There are thus using data to improve the efficiency and reduce the cost structure of air industry operations. Read more at: http://www.networkworld.com/article/2944535/big-data-business-intelligence/big-data-enables-an-entirely-new-design-of-airport.html

Just like the earlier days, even now we view healthcare solutions in two-dimensional ways – patient-doctor relationship or technology revolutionizing patient’s health and wellness. The problem gets more acute with invention of new technology solutions. But if we don’t intervene to gather the data and use them, there’s no use of new technologies such as wearable devices. Thus real collaboration is required where every member connected to the patient acting as a crew member can steer the patient towards possible better health. Everyone working collaboratively can harness the power of technology and big data, to deliver a 360 degree-solution built around the patient. Implementing the approach of multi-stakeholder interaction of social media, can make true social healthcare realize its potential. Read more at:  http://www.socialmediatoday.com/social-business/paul-tunnah/2015-07-09/effective-healthcare-requires-social-approach

Big Data is a resource that helps organizations to understand and take control or corrective action to address problem such as customer centric service delivery, by accurately joining big data with Master Data Management (MDM). MDM helps to control the momentum of incoming data and tools that applied in MDM helps to verify facts about customers, vendors and products. Data definitions and rules previously established by the corporation are reflected in the MDM. Service Oriented Architecture (SOA), due to its agile nature, plays a key role in the corporation achieving its vision.
There is a symbiotic relationship between MDM and SOA. SOA provides the filtering needed for a steady stream of consistent data, which is an important aspect of data mining as the quality of data derived determines the accuracy of predictions.
Thus MDM is a valuable tool as it has the capacity to store and analyze large volumes of data to discover new patterns which leads to an increase in profitability.

For more information visit:
http://www.finextra.com/blogs/fullblog.aspx?blogid=11073

Today, fast and accurate decisions are critical for an organization's success. But there is a risk of incorrect decisions if we rely on approximate sciences such as intuition and judgment of individual decision makers. The value of data can be realized only once a coherent ‘data strategy’ is established. A data strategy requires an organization to embed and integrate data analytics into the process of decision-making. The organization must seek and utilize data based insights that are most fruitful. Big Data demands a tighter integration of business functions and better mechanisms for integration. Evidently, various teams shall work together to understand and exploit cross-functional data. Identifying key data gaps and taking collective decisions for data gathering will ensure that specifically data with potentially useful information is collected. Read more at: http://www.bobsguide.com/guide/news/2015/Jul/13/big-data-small-data-and-fast-data-using-data-to-drive-better-decisions.html

SME’s have a large number of advantages in using big data technology and it is found to play an important role for them recently. Firstly it is important to understand that what big data is. Big Data is defined as a popular term to describe exponential growth and availability of data, both structured and unstructured and is important for businesses. It is a series of combined data lakes used for more accurate analyses. SME’s should move to Big Data storage solutions because storing the new data generated each day is becoming expensive for the companies and its increasing their costs. When SME’s start using such combined datasets, they will have enough data to analyse and improve their decision making. Interest in big data has reached new heights for SME’s as they take their chances of capturing more information from everywhere possible. SME’s can also use big data to attract new customers, tap new markets and reduce costs. Some more ways how big data technology can help SME’s prosper are by using big data tools which increase their ability to use predictive analytics for decision making. It also helps SME’s move unused data into different less expensive places. Hence SME’s should definitely be looking forward to such big data technology for improved performance.

Read more at: http://www.smartdatacollective.com/bruce-robbins/329520/big-data-smes

The term Big Data has become popular recently and is used to define exponential data development and availability, both structured and unstructured. Big data is crucial to businesses since more data implies precise analyses which results in efficient decision making, reduced risk and cost reduction. Big Data is used for more complex datasets and refers to application of predictive analytics and other advanced application tools to derive the results and seldom to the size of datasets. The three V’s of Big Data are namely: Volume, Velocity, and Variety. Apart from increasing varieties and velocities of data, data flows are very challenging. Variability, complexity are some other factors of Big Data. Data flows in from different sources and it’s difficult to connect them which has become a huge task these days. Big Data has become necessary for companies which helps them stay updated with the new technologies. Processing the Big Data smartly and accurately is worth a lot of income for the companies. Big Data demands amazing technologies to efficiently process such datasets in given deadlines. There were companies who spend a lot of money on data analytics and other management systems to increase their efficiency. Recently Big Data has increased the need for information organizations. Big Data also helps to grow and continue increasing the number of servers used which only adds to expenses of the company.

Read more at: http://www.smartdatacollective.com/anandsrivastava1988/328749/what-big-data-and-how-useful-it