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Enterprise Resource Planning Dashboard Example - Enterprise resource planning (ERP) systems help businesses manage the important parts of their operations. These systems unite internal and external management information across an organization through various software applications. The end goal is to gather information required to meet corporate objectives. ERP systems run on a wide range of computer hardware and network set ups, using a database to store vital information. Research shows that an ERP system typically includes the following three distinctions: A system that functions in real time (or as close to real time as possible)...
Fitness Centers Data Mash Up - An analyst at a chain of fitness centers may mash up various data sources to gain insights into member behavior, operational performance, and overall business health. These data sources provide a comprehensive view of the business and help inform decision-making across different functional areas. Here are some common data sources that an analyst at a chain of fitness centers might mash up: Membership Data: Membership data includes information about members' demographics, membership plans, membership tenure, and membership status. By analyzing membership data, analysts can identify trends in member acquisition and retention, segment members based on demographics or behavior, and tailor marketing strategies to target specific customer segments. Attendance Data: Attendance data tracks the number of visits and participation rates at different fitness center locations and classes. By analyzing attendance patterns, analysts can identify peak hours, popular classes, and trends in member engagement. This information can help optimize facility operations, staffing levels, and class schedules to meet member demand and maximize utilization...
Future or Historical Analytics - Now this doesn't preclude that combination from also going back, in this case it's shown as another database, but in effect going back to a data warehouse for our future or historical analytics. And in this process, data virtualization is accessing and converting semi-structured data providing a faster way to transform, match and integrate this as opposed to ETL'ing all of this, which would then introduce latency. Also it provides for the capabilities for data management. The general benefit of this was faster access to up to date information and the creation of more BI type reporting type projects in significantly less time as was capable previously. Then after the benefits were realized for Sales and Finance, it was being replicated in many other departments, such as in the HR area, or in lot of the G&A functions within this company. This company has a philosophy that the majority of their money should go into developing new drugs, so IT's role was to reduce the cost, but increase the efficiency of all G&A functions. So they took a lot of those data process and applied virtualization...
How Does Data Grid Cache Employ In-Memory Database Technology? - A data grid cache intelligently queries and saves the data necessary to support a given dashboard or data visualization, including all filtering and drill-down levels. When a cluster of commodity-priced servers is used to run a data grid cache, the data file is automatically split into chunks and distributed to the nodes. One data chunk may be copied to multiple nodes, so if some nodes fail, the cluster could still work in most cases. On each node, the dimensions are always loaded into memory when executing the query. Measures are loaded into memory in chunks...
Showing a Data Mashup Tool - So what is a data mashup tool? First of all, what you see in front, it looks like an Excel spreadsheet, but it has nothing to do with Excel, it's just a grid. How do I access my data? I select my query node, and I see a list of all my data sources. A data source could be a relational database like Oracle, SQL Server, or DB2. It could be a flat file. It could be a Web service. It could be an XML file, or even be another API. So we are very flexible in terms of the kind of data we can access. We can access almost any kind of data. I choose my data source. Now how would you expose the data to your developers, to your file users? You have two options, option one, you can create one or more predefined queries, you can just drag and drop fields for the basis of the visualization. Now the problem with query is that it's a fixed result set, so it's hard to envision every possible used case, every possible requirement upfront...
List of Data Visualization Chart Types - A Pareto chart is a type of graph that is used to represent the distribution of data in which the majority of the observations are concentrated in a few categories. It is named after Italian economist Vilfredo Pareto, who first described the concept of the 80/20 rule, which states that 80% of the effects come from 20% of the causes. In a Pareto chart, the categories are arranged in descending order of frequency or magnitude, with a bar graph showing the relative frequency or size of each category, and a line graph showing the cumulative total. The chart is used to identify and prioritize the most important factors in a given situation, and can be applied in a wide range of fields, including quality control, business analysis, and process improvement...