J.R. Paik

  The logistic industry and, especially, delivery services, have had an extremely unenviable reputation over the years. So many packages were delayed. So many annoyed customers complained and cracked jokes about the sluggishness of delivery services worldwide.  Meanwhile, only a few knew how many challenges such services face during their work and on the last mile in particular. Traffic jams, confusion on overloaded warehouses, and poor route planning are just a few of them. However, when it seemed that the stigma wouldn't come out, Big Data came into play. Paired with special technologies and software, it brought many positive changes and transformed the logistic industry once and for all. So what is big data, and why does it have such influence on logistics? let’s get to the heart of the matter and find out by the following points: The definition of Big Data & its major characteristics; The benefits of implementing Big Data in logistics; The impact Big Data has on the logisti

  The term "data quality" on the search engine results in six million pages, which clearly expresses the importance of data quality and its crucial role in the decision-making context. However, understanding the data helps classify and qualify it for effective use in the required scenario.  Understanding the Quality of Data Good quality data is accurate, consistent, and scalable. Data should also be helpful in decision-making, operations, and planning. On the other hand, lousy quality data can cause a delay in deploying a new system, damaged reputation, low productivity, poor decision-making, and loss of revenue. According to a report by  The Data Warehousing Institute , poor quality customer data costs U.S. businesses approximately $611 billion per year. The research also found that 40 percent of firms have suffered losses due to insufficient data quality.  Organizations worldwide are heavily investing in data management and processing to achieve good quality data, but the r

  Before We Begin: In this tutorial, we will configure this application with the following components in mind: The microservice application will be a Mavenized Java application. We will use MySQL DB Server as a relational database. The JDBC data source will be a transactional data source ( XADataSource ). JDBC Driver Library Configuration With Maven You need a JDBC driver to connect your Java application with a relational database. The driver is usually provided by the database vendor. Fortunately, most database vendors have released their JDBC drivers to a Maven repository. If you use Maven to build your application, you can add your JDBC driver by adding code that is similar to the following example to your  pom.xml  file. XML 1 < dependencyManagement > 2 < dependencies > 3 <!-- https://mvnrepository.com/artifact/mysql/mysql-connector-java --> 4 < dependency > 5 < groupId > mysql </ groupId > 6