By making use of excess of data available and information and communication technologies (ICT), smart cities can now address the various economic, spatial, social and ecological problems. Although data analytics forms the core of business strategies, yet very little is known about new business models within smart cities and urban living. Recent advances in Data Analytics have shown promise than city data analysis and its use can generate value for municipalities, companies and individuals. From relatively simpler analytics techniques to more sophisticated one, the available tools can adopted to obtain the desired results. For example, when the enormous volume of the data poses serious challenge, clustering technique can make the dataset manageable. Read more:- https://icrunchdatanews.com/smart-data-analytics-smart-cities/

At a time when software is at forefront of all business activities, it is surprising to know that very few business minds truly comprehend the practice of software development and options that are available to them. Among the two most widely used methodologies-Agile and waterfall, picking up the suitable one and adoption of the same is extremely crucial for business. However the responsive and flexible nature of agile methodology is what is desired at present day businesses and for this reason agile is fast becoming the preferred approach. Continuous communication and collaboration, minimal documentation, increased efficiency are some of advantages of agile methodology. Read more:  http://www.information-age.com/technology/applications-and-development/123459702/how-being-more-agile-can-help-you-juggle-your-business-demands-more-efficiently

With more than three million Americans being affected with Hepatitis C Virus (HCV) and the virus posing serious challenges to reducing the costs of disease management and control, recent research from University of Michigan is promising some hope. By making the use basic EHR data, predictive analytics algorithms can now flag the affected patients who are at high risk of developing complications from the virus. Although one-third of the HCV patients are at risk, all the patients are treated which lead to huge unnecessary healthcare spending. This is where the predictive analytics model is expected to be of great use. Further integration of the model with EHR will enable the providers to deliver more targeted treatment and a chronic disease management plan can chalked out. Read more :- http://healthitanalytics.com/news/predictive-analytics-identify-high-risk-hepatitis-c-patients

Just like other areas of economy, marketing, too, has been impacted significantly by the growth of data analytics. Although the importance of analytics has been recognized in marketing, yet it is observed that in most cases the tools are not being used efficiently. For this, aligning data with the goals of the company needs to be done. Secondly, the smooth transition from big data to useful data and determination of the relevant metrics and adoption of those metrics are required. And last but not the least, hiring of the right people with analytical and creative minds to properly use the data is imperative. Read more: http://www.forbes.com/sites/johnrampton/2015/06/21/how-can-cmos-make-sense-of-big-data/

Rapidly changing consumer demands are becoming one of the major concerns of the financial institutions. Analytics is the technology which can be adopted to address this need. With evolving customer expectations, analytics solutions, too, have adapted, but the question under consideration is whether the banks are prepared to adopt and benefit from the next-generation analytics solution. As viewed by Thomas H. Davenport, evolution of analytics is a three-stage process of which Analytics version 3 is the latest generation which merges qualities of previous technologies and focuses on prescriptive analytics. Based on the data collected, Analytics 3.0 will enable the financial institutions can create tailor made services for customers. However, to fully reap the benefits, the institutions have to make sure that the right technologies and practices are in place. Read More at: http://internationalbanker.com/banking/are-banks-ready-for-next-generation-analytics/

When it comes to risk management, it is often observed that the companies either implement blanket management programs applying the same strategies to all employees, or use the "squeaky wheel approach" focusing primarily on at-risk employees. However, both the approaches result in inefficiency. Thus, a strategic employee-specific management program can be adopted to identify the at-risk employees. Such a program monitors the employees for subtle and almost undetectable changes that are indicative of risky behavior and this is where predictive analytics model is of immense help. Predictive modeling enables the manager to identify not only the high-risk employees, but also the cause behind a particular incident.  Predictive modeling is fast becoming an indispensable tool for mitigating risk, retaining top talent, and building long-lasting relationship with the employees. Read More:- http://www.natlawreview.com/article/mitigating-risk-predictive-modeling

Though underestimated at times, social media marketing is fast becoming a vital necessity for success of business. Due to complexity of the nature of data analysis and increasing number of social media platforms available, the task of adopting the best social strategy may appear confusing. For more productive use of social media for marketing, the author suggests the following: 1) Creating outstanding and attractive content like images, text documents, etc. 2) Adopting social marketing instead of impersonal digital marketing.  3) Developing two way communication channels with the customers.4) Doing proper research. 5) Monitoring social media 6) Being genuine Read more:-  http://www.business2community.com/social-media/key-to-mastering-social-media-marketing-01248568

Focused market research is imperative for building of brands and foundation for market research is laid down by market intelligence. In broad terms, market intelligence collates three types of information- business, market and competitive. For distribution of information, social media is playing a huge role. Thus integration of marketing intelligence with social media monitoring and digital space opens up many channels of opportunities to address specific business issues and enhance performance significantly. However, this requires intense understanding and customization of data. Also, digitization of field resources poses certain challenges. On a concluding note, the authors, Stephen Dale and Melissa Chue are of opinion that market intelligence should ultimately serve as be the backbone of any organization and more investment should be made to expand digital resources and data. Read more:- http://www.marketing-interactive.com/events/intelligence-bedrock-good-market-research/

Faced with challenges of bureaucratic vices and realities, government agencies often let things slip through the cracks, including fraud. It is disheartening to learn that huge losses are incurred by many public facing agencies due to fraud and such losses are regarded as expected operating costs. Yet, no measures are being employed. Thankfully, investments are being made in predictive analytics tools by agencies and some progress has been achieved in detecting preventing and prosecuting fraud. However, to tackle crimes effectively the tools need to be comprehensive, flexible and affordable. For example, dynamic case management solutions can be applied to tackle the mammoth challenges faced by the agencies. Read more: http://gcn.com/articles/2015/06/10/fraud-control.aspx

With significant increase in online sales and more customers opting to purchase through mobile devices, high street retailers are facing difficult times. No wonder it is time to elevate shopping experience to a whole new level. Though Retails Analytics is not a new concept, the approach faces challenges in brick-and-mortar stores. Investing in real-time Wi-Fi analytics, where modern in-store analytics technologies can integrate with existing in-store Wi-Fi infrastructure to capture precise and real-time customer behaviour in stores, can be a solution. Creating an inclusive shopping experience that effectively combines the online and offline experience is the need of the hour. Read More at: http://www.fourthsource.com/mobile/future-analytics-retail-19148

The Internet of Things has the ability to benefit the healthcare sector vastly in the future. With EHR clinical analytics and sophisticated machine learning combining with big data from wearable, home monitors, medical devices, the Internet of Things has a huge potential for creating a productive environment of predictive analytics and prescriptive insights. Yet the concept is met not without challenges. In order to successfully reap the benefits, Jennifer Bresnick suggests development of certain core competencies, like "Developing the Mindset", "Building the health IT infrastructure" and others. Read More at: http://healthitanalytics.com/news/five-core-competencies-for-the-healthcare-internet-of-things

Big Data Analytics has started to make significant strides in less explored areas like improving manufacturing performance. No wonder the theme of ARC European Forum, 2015 was intended to help develop some clarity over emerging related concepts such as Industrie 4.0 and the Industrial Internet of Things (IIoT). Several use cases about how "applying these concepts can deliver tangible benefits in real-world industrial production across a broad cross-section of industrial sectors" were presented. Read More at: http://www.automationworld.com/industrial-internet-things/big-data-analytics-improve-manufacturing-performance

Predictive Analytics is making its entry into the toolbox of small companies. Predictive Analysis is a three-part formula- analysis of past performance of situation under consideration, understanding the present and applying the past to present to predict the future. For small businesses, it can be applied for customer retention, target marketing, demand forecasting, and overall marketing. However, it is crucial to ascertain the purpose for using Predictive Analysis, as the technology may not necessarily be right for every company or for every situation in the small business sector. Read more at: http://www.smallbusinesscomputing.com/News/Marketing/can-predictive-analytics-help-your-small-business.html