Business intelligence applications provide historical, current and predictive views of business operations. Common functions of Business Intelligence technology include building data warehouses, online reporting, predictive analytics, data mining and presenting business performance in dashboards.
Database usage over a long period of time can cause database performance degradation. The decrease in database performance is likely caused by data fragmentation or because there is no longer a match between the database configuration and the current data, load and usage. It is necessary to anticipate so that this performance decline does not lead to a database failure.
With experience in handling performance tuning projects for databases larger than 1 TB and containing hundreds of millions of records, CJT has specialized techniques for improving database performance when standard configurations are no longer sufficient.
The project begins with an assessment of the database configuration and an analysis of the load on the database, allowing us to provide appropriate recommendations for improving your database server performance. Performance improvements were essential to ensure the database, data warehouse, and data model would not cause slowdowns in the reporting system.
Database archiving is the process of moving old or unused data from the operational database to a separate storage system, where it can be accessed for future reference or analysis. Database archiving can help improve the performance, security, and scalability of the database, as well as reduce the costs and risks of data retention and compliance.
A database archive used to retain historical data from retired applications or for other purposes such as merger and acquisition archiving, e-discovery data storage, and business intelligence data preservation. It serves as the official version of the data and is a valuable solution for various data retention needs.
A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. The data within a data warehouse is usually derived from a wide range of sources such as application log files and transaction applications.
A data warehouse centralizes and consolidates large amounts of data from multiple sources. Its analytical capabilities allow organizations to derive valuable business insights from their data to improve decision-making. Over time, it builds a historical record that can be invaluable to data scientists and business analysts. Because of these capabilities, a data warehouse can be considered an organization’s “single source of truth.”
Data model offers online analytical processing (OLAP) and data mining capabilities, enabling business users to make sense of the data stored across their data warehouses. It enables organizations to pull data from across the organization, analyze it, then make data-driven business decisions. It provides enterprise-grade semantic data models for business reports and client applications such as IBM Cognos Analytics, Microsoft Power BI, Salesforce Tableau, Microsoft Excel, and other data visualization tools.
An OLAP cube helps to optimize data. It is also used to analyze data quickly. These functionalities make cubes a crucial component of an effective data warehouse solution.
Data reporting refers to the process of collecting data from various sources and then presenting it into meaningful information to gain valuable insights into your business performance.
Once the collected data is taken from multiple sources, organized, and visualized, you can perform data analysis to assess the current status of your organization and create actionable plans or provide recommendations on future activities based on this data. Thus, data reporting is practically a step towards data analysis.
For office and factory customers, CJT develop Microsoft Power BI-based dashboards and reports by sourcing data from data warehouses or data models. The resulting reports can be accessed from anywhere on a variety of devices for various purposes, such as monitoring performance: finance, sales, production, shipping; and even decision-making for top management.
Data analytics examines, cleanses, transforms, and models data to extract insights and support decision-making. As a data analyst, your role involves dissecting vast data sets, uncovering hidden patterns, and translating numbers into actionable information. Organizations can use data analytics to make better decisions, improve efficiency, and predict future consequences.
Data analytics plays a critical role in today’s data-driven world. Data analytics helps organizations harness the power of data, enabling them to make decisions, optimize processes, and gain a competitive advantage. By transforming raw data into meaningful insights, data analytics empowers businesses to identify opportunities, mitigate risks, and improve their overall performance.
Data mining is the process of sorting through large data sets to identify patterns and relationships that can help solve business problems through data. The process of collecting and extracting information can be done using data science and artificial intelligence. Data mining is often also called Knowledge Discovery in Database. Warehousing is an important aspect of data mining.
Data mining has a wide range of applications across various industries, including marketing, finance, factory and mining. For example, in marketing, data mining can be used to identify customer segments and target marketing campaigns.
To meet further needs for data processing and reporting, CJT developed dashboard applications (desktop, web, and also mobile) according to customer needs. A dashboard is an information management tool that provides a visual representation of real-time data that helps business users make smarter, data-driven decisions. The interactive tool allows users to collect complex data from multiple sources and turn it into easy-to-digest data visualizations. They are the perfect vehicle for delivering KPIs and helping teams track the progress they’ve made to achieve a goal.
In addition to the above, a dashboard can be particularly useful when it provides data in real time, automatically updating with the latest information. Having real-time data is pertinent to many businesses, especially app marketers who desire to optimize their campaigns as fast as possible for maximum success.