Introduction to Big Data and Business Analytics

The term big data has come due to rapid generation of data in various organizations. In big data, the big is the buzzword. Here the data are so large and complex that the traditional database applications are not able to process (i.e., they are inadequate to deal with such volume of data). Usually the big data are described by 5Vs (volume, velocity, variety, variability, veracity). The big data can be structured, semi-structured, or unstructured. Big data analytics is the process to uncover hidden patterns, unknown correlations, predict the future values from large and complex data sets. In this chapter, the following topics will be covered more in detail. History of big data and business analytics, big data analytics technologies and tools, and big data analytics uses and challenges.

A Multi-Replica Centered Commit Protocol for Distributed Real-Time and Embedded Applications

Modern multi-site database applications are not only time-driven but also require efficient quality of services with no single-node failure. It might be ideally achieved using database replication techniques. The transactions, being a basic component of these applications, are more likely to miss their deadlines because of requiring unpredictably long time to access remote data items. The temporal validity of data is another issue requiring attention to be paid. To address these problems, a Cluster-Replicas with Efficient Distributed Lazy Update (CRED) protocol is proposed in this paper. The CRED protocol increases the chance of timely execution of transactions and data freshness in an unpredictable workload environment by utilizing the lazy replica update strategy. It reduces the negative impact of the burst workload with a marginal overhead of ensuring timely-updated replicas. The simulation results confirm that the CRED outperforms the ORDER protocol by up to 4%.

A Multi-Replica-Centered Commit Protocol for Distributed Real-Time and Embedded Applications

Modern multi-site database applications are not only time-driven but also require efficient quality of services with no single-node failure. It might be ideally achieved using database replication techniques. The transactions, being a basic component of these applications, are more likely to miss their deadlines because of requiring unpredictably long time to access remote data items. The temporal validity of data is another issue requiring attention to be paid. To address these problems, a Cluster-Replicas with Efficient Distributed Lazy Update (CRED) protocol is proposed in this paper. The CRED protocol increases the chance of timely execution of transactions and data freshness in an unpredictable workload environment by utilizing the lazy replica update strategy. It reduces the negative impact of the burst workload with a marginal overhead of ensuring timely-updated replicas. The simulation results confirm that the CRED outperforms the ORDER protocol by up to 4%.

Novel Approach to Transform Unstructured Healthcare Data to Structured Data

With the rapid growth in number and dimension of databases and database applications in Healthcare records, it is necessary to design a system to achieve automatic extraction of facts from huge table. At the same point, there is a provocation in controlling unstructured data as it highly difficult to analyze and extract actionable intelligence. Preprocessing is an important task and critical step in Text Mining, Regular Expression and Information retrieval. The accession of key data from unstructured data is often difficult. The objective of this project is to transform the unstructured healthcare data to structured data particularly to gain perception and to generate appropriate structured data.

PERANCANGAN APLIKASI DATA IKLIM-71 DI STASIUN KLIMATOLOGI KLAS I PULAU BAAI – BENGKULU

Climatology Station Class I PulauBaai Bengkulu under the auspices of the Meteorology, Climatology and Geophysics which produce so many daily weather data are not computerized well. By this author wants to help the staff to facilitate the observation of the results of the data contained in Baai Island Climatology Station Bengkulu. Based on these reasons make the authors develop a design data applications FKlim-71 computerized to help resolve some of the problems that often occur. In making this application there are some required data is data such as temperature, rainfall data, the data of solar radiation, a special weather event data, the air pressure data, the data humidity, and wind data.Application design is intended for Climatology Station Class I Baai Island Bengkulu because there making this application done. This application uses Microsoft Visual Basic programming language and MySQL as the database.The test proved that the application program database applications Fklim-71 can facilitate the performance of observer Climatology Station Class I PulauBaai Bengkulu.

An approach to information export from database for complex master-detail table hierarchies into a single flat table form

When developing a database client application it is usually required to implement a capability to export information from database tables into some simple data-exchange representations of tables like the CSV (Comma-Separated Values) format. It is very straightforward to implement the export for a single database table. But some information about the records of a master table may be represented by the records from, sometimes, several detail tables, so the resulting CSV table would be incomplete without this information. We develop AIS (automated information systems) using declarative specifications of database applications (SDA). The AIS’es are implemented using general algorithms, which are directed by the specifications. In this article we’ll consider the approach to generation of flat tables from the master-detail groups of tables, which allows users to represent compactly the data from a hierarchy of tables related by the master-detail relationships and to select conveniently which kind of information to include into the resulting table.