The Use of Big Data in Marketing Analytics

Big data has broken through the public imagination, has revolutionised the process through which business find innovative ways, and has transformed the data into valuable information that will shape business intelligence and gain business insights to make better decisions. The purpose of this study is to review the development of big data, architecture, and the use of big data in marketing analytics. From the analysis of literature reviews, a big data in marketing analytics model has been proposed. In using big data in marketing, marketers need balanced analytics and then identify opportunities for improvement based on reporting or analysing past and present big data to predict and influence the future.

ENTERPRISE ARCHITECTURE SEBAGAI STRATEGI DALAM OPTIMALISASI PROSES DAN TEKNOLOGI MENGGUNAKAN TOGAF ADM

PT XYZ merupakan perusahaan yang menawarkan audit pihak ketiga untuk menyediakan jasa sertifikasi sumberdaya alam dan lingkungan. Dalam menjalankan perusahaannya, PT XYZ memiliki layanan utama pada fungsi sertifikasi yaitu Audit Sertifikasi dan Penerbitan Dokumen Legalitas. Seiring dengan kemajuan teknologi informasi dan komunikasi, PT XYZ memiliki beberapa kendala dan membutuhkan strategi teknologi informasi yang tepat untuk menyelesaikan permasalahannya. Pertukaran data yang belum efektif merupakan salah satu kendala yang terjadi di fungsi sertifikasi yang menyebabkan munculnya keluhan pelanggan terhadap kecepatan layanan. Dalam penelitian ini akan membahas perancangan Enterprise Architecture sebagai strategi dalam optimalisasi proses dan teknologi menggunakan TOGAF ADM. Perancangan tersebut dimulai dari preliminary phase, architecture vision, business architecture, data architecture, application architecture, technology architecture, opportunities and solution, dan migration planning. Dengan blueprint dan IT Roadmap sebagai hasil akhir dari penelitian ini, diharapkan akan membantu PT XYZ dalam menyelesaikan permasalahannya segaligus menjadi strategi dalam optimalisasi proses dan teknologi yang tepat.

ENTERPRISE ARCHITECTURE DESIGN USING ENTERPRISE ARCHITECTURE PLANNING (EAP) METHOD IN KELURAHAN SINDANGJAYA OFFICE MANDALAJATI DISTRICT BANDUNG CITY

In today's information era, the ability to do business or carry out activities is reliant on the availability of information technology is needed in most of the business sector. Along with the expansion of information technology, however, it frequently introduces new problems such as data redundancy, technological platforms, and excessive information technology spending. To avoid the problem that frequently happens, organizations require IS planning that may create alignment between IT and the business. Enterprise Architecture Planning (EAP) is a Zachman Framework-based Enterprise architecture methodology. The first stage is Planning Initialization, which aims to design information technology for the future utilizing the Enterprise Architecture Planning (EAP) process (starting), second, we'll look at business modeling, systems, and present technology (where we are now) , third, data architecture, applications, and technology (recommendations), and fourth, implementation (Achievements). The existence of a recommendation or blueprint given to the Sindangjaya Ward Office is expected to solve in the resolution of problems at the ward office, and it is hoped that the method used can be applied and understood when the need for future development, particularly in the IT field.

Real Time Traffic Prediction Based On Social Media Text Data Using Deep Learning

Due to urbanization Traffic management is one of the major issues in contemporary civic management, considering this circumstance traffic analysis is turning into the need of the present world. Text data generated by Twitter, Facebook and other social media platforms can be used for traffic management. Big data helps in traffic prediction and traffic analysis of advancing metropolitan zones. Constant traffic investigation requires preparing of information streams that are produced persistently to increase fast experiences. To measures stream information at a fast rate advancements on high figuring limit is required. Social media text data can be processed by using batch processing and stream processing with big data architecture through Spark and Hadoop framework. In this paper big data architecture is proposed for real time traffic text data analysis. In architecture Spark and Kafka are used in combination. Kafka helps in pipelines text data used in conjunction with spark stream processing engine. Big data architecture using Spark, Kafka with ability for processing and preparing huge measure of information, have settled the serious issue of handling and putting away constantly streaming data. The traffic information from Twitter API is streamed. In The proposed model pointed toward ensemble neural network model to reduce the variance in results for better prediction foreseeing traffic stream text data by incorporating Spark and Kafka that will be of an extraordinary incentive to the public authority for traffic management and analysis.

Internet of Things: A Review of Functionality, Applications, Architectures and Challenges

The Internet of Things (IoT) is an emerging paradigm that embodies the vision of merging smart objects while utilizing the internet as the backbone of the communication system to establish a smart interaction among physical entities in pervasive environments. In IoT, data is generated in realtime and stored in permanent repositories. Additional data in the form of meta-data that describes things adds to the data volume and to manage this data, architecture is required. IoT finds its applicability in a plethora of applications such as transportation, smart city, smart health, smart environment, home entertainment, sports, etc. but there is no universal architecture for all IoT implementations. We have layered architectures and domain-specific architectures for different IoT applications. Besides a large number of architectures for IoT, it faces several potential challenges such as scalability, reliability, heterogeneity, etc. This paper presents an understanding of the Internet of Things in terms of its functionality, layered and domain-specific architectures, and its potential challenges.