The business success is critical for any organization irrespective of its size. Understanding business value and advanced technology capabilities in Business Intelligence (BI) solutions for analysis and decision making is the need of every management, researchers and analysts. Data is available at every corner, at every platform and it is being produced all the way using digital equipment. These complex data sets for analysis and decision-making can be used on various platforms and are more accessible than ever to find insights and explanations. There is an abundance of datasets and data analysts, but organizations are still unable to leverage its potential to the fullest and this perhaps is the failure of most data analytics initiatives. This paper covers the need for Augmented Analytics adoption in companies to maximize business value with respect to added advanced analytics capabilities in BI Tools for effective, accurate and timely decision making, and business analysis.

Our Indian government has set a goal of creating 100 smart cities that will use smart technology such as smart grids, smart phones, and various monitoring devices to generate large amount of data. Traditionally, data centres have been in charge of these files. One of the most pressing issues in data centres is resource management. One efficient strategy to address this issue is to use the best method for handling data, and when we're talking about Smart Cities, which will create a big quantity of data, it's becoming increasingly important to manage this massive amount of data. It is also necessary to provide the better living standard for every citizen in the smart cities by providing good safety and security to them as well. As we know that every citizen is not smart enough to protect himself against the physical as well as cyber-crimes. In this paper, we have designed an advanced Artificial Intelligence (AI) based safety and security system for the human beings and their personal data in a smart city. The system architecture is designed with AI module with machine learning algorithms, IoT technology and sensors, smart drones, intelligent video surveillances, data analytics and cyber security modules. This system can efficiently protect the citizens and their personal data against the criminals with high speed and accuracy.

Now a day the world is mobile and internet oriented, each and every person must have the both of things. While in using the mobile and internet we have to face many problems such as malware attacks in while in sending and receiving message. We consider a malware attack in sending an MMS and Bluetooth. We found many problems while sending message we used distributed algorithm and dummy signature to protect the message from malware [3].In mobile network malware attacks frequently occur while sending and receiving information [2]. Develop an efficient system to protect infection and infected nodes to recover and produce dummy signature to overcome of spreading and outbreaks of malware [1]. We found that the problem is how to optimally distribute content-based signature of malware, that help to detect malware and disable further propagation to minimize the no of infected nodes[4]. we can go through two different approaches 1. MMS 2. Bluetooth. In MMS a malware send a copy of itself to all devices whose numbers are found in address book of infected device. We use optimal distributed solution to efficiently avoid malware spreading and apply dummy signature to help infected nodes to recover [1].

The study of perturbation based Privacy Preserving Data Mining (PPDM) [1] [2] approaches introduces random perturbation that is number of changes made in the original data. The limitation of existing work is single level trust on data miners but proposed work is focus on perturbation based PPDM to multilevel trust.[1] When data owner sends number of perturbated copy to the trusted third party, adversary cannot find the original copy from the perturbated copy means the adversary diverse from original copy this is known as the diversity attack. To prevent diversity attack is main goal of Multilevel Trust in Privacy Preserving Data Mining (MLT-PPDM) services.[1]The different MLT-PPDM algorithms are used to produce noise into original data. In existing system by applying nonlinear collusion attack on MLT-PPDM approach, it is possible to reconstruct original data. In proposed system by applying masking noise linear transformation algorithm which produce noise into original data. When same nonlinear collusion attack is applied on proposed approach it cannot reconstruct original data means it preserve the privacy. That means existing system is limited only for linear attack.[1] But proposed system is working on the non-linear attack also. Linear attack is calculating average between all perturbated copies. Nonlinear attack is calculating minimum, maximum, median function estimation.

Cloud computing is one of the rising and encouraging field in Information Technology. It provides services to an organization over a network with the ability to scale up or down their service requirements. Cloud computing services are established and provided by a third party, who having the infrastructure. Cloud computing having number of benefits but the most organizations are worried for accepting it due to security issues and challenges having with the cloud. Security requirements required at the enterprise level forces to design models that solves the organizational and distributed aspects of information usage. Such models need to present the security policies intended to protect information against unauthorized access and modification stored in a cloud. The work describe the way for modeling the security requirements from the view of tasks performed in an organization by using the cryptography concepts to store data on cloud with the less time and cost for process of encryption and decryption. In this work, the RSA and AES algorithms are used for encryption and decryption of data. The role based access control model is used to provide accessibility according to the role assigned to the user. This paper has the mathematical model for the trust calculation of the user. This system gives the rights for uploading to the user when he/she is authorized by the Administrator and Owner.