Show
If you have been following the IT field and developments, especially on infrastructure management and server processes, you no doubt have heard about data warehousing. Simply put, Data Warehousing is the process of storing large volumes of data across the enterprise. In recent years, Data warehousing modernization has made it possible for companies to store their information and analyze it in-house instead of just purchasing services from cloud service providers. This modernization is driven by recent advances in data warehousing technology. In the last two decades, Data Warehousing (DW) has grown substantially to become a unique component of the modern enterprise architecture. It builds on the concept of ETL (extract-transform-load) that combines data from multiple sources into a centralized repository for analysis and reporting. As enterprises have evolved to embrace new business models, thrive in the digital economy, and establish greater organizational agility, data warehousing has grown in importance to support multidimensional decision-making across the enterprise. Data warehousing is changing rapidly, with the advent of big data, cloud computing and business intelligence (bi). For example, many companies have opted not to build their own warehouse management system and have switched to using cloud-based systems to store all their data. However, there are still some organizations who prefer to manage their data on-premises rather than in the cloud. Moreover, big data are changing the future of data warehousing, while novel bi tools enable more sophisticated processing of very large amounts of structured, unstructured and semi-structured data. Also, with the advent of modern data warehousing techniques and advanced analytics that serve as a perfect blend of historical and real-time information, enterprises gain timely support in their decision making. Overall, new age data warehousing is being driven by the new era of digital technologies, which enable the development and deployment of advanced data mining and data analytics functionalities. Data Warehousing or something else. Let's help you with your IT project. Data Warehouse Modernization TechnologiesWith the ever-increasing compute and storage needs of today’s organizations, the challenge faced by businesses is the spiraling cost of managing data storage. Hence, the modern data warehouse must be equipped with scalable and high-performance tools that make it easy to store, analyze and visualize data. Scalability, performance, and quality of service in modern data warehouses is mainly driven by the following cutting edge digital technologies:
As data warehouses revolutionize business intelligence and analytics, new trends are emerging by virtue of the latest advancements in data warehousing. Modern data warehouses have ergonomic and easy to use business intelligence tools, offer real-time analytics functionalities, and can be deployed within clouds to benefit from the capacity, scalability, and quality of service of cloud computing. Data Warehousing BenefitsModern enterprises invest in data warehousing infrastructure to enhance their ability to manage large amounts of data from diverse sources. With a state-of-the-art data warehousing infrastructure in place, companies can enjoy the following benefits:
In recent years many organizations understand the value of data warehouses in terms of offering a centralized location for managing project data and operations. Nevertheless, many companies struggle with how to best leverage their resources to meet the demands of ever-changing environments. It is not uncommon for many businesses to feel overwhelmed by the idea of implementing data warehousing due to its perceived complexity, especially when it involves merging disparate sources and putting the new information into a warehouse structure. Therefore, CIO (Chief Information Officers) must strive to raise awareness about the complexity and the multi-facet benefits of modern data warehouse software solutions. Recent PostsWhat is a data warehouse What are the four key factors that make it a data warehouse?A typical data warehouse has four main components: a central database, ETL (extract, transform, load) tools, metadata, and access tools. All of these components are engineered for speed so that you can get results quickly and analyze data on the fly.
What are the three main steps involved with getting data into a data warehouse?7 Steps to Data Warehousing. Step 1: Determine Business Objectives. ... . Step 2: Collect and Analyze Information. ... . Step 3: Identify Core Business Processes. ... . Step 4: Construct a Conceptual Data Model. ... . Step 5: Locate Data Sources and Plan Data Transformations. ... . Step 6: Set Tracking Duration. ... . Step 7: Implement the Plan.. Which of the following is true of a data warehouse quizlet?Which of the following is true of data warehouses? Data warehouses are created when companies begin to store vast amounts of data in database systems separate from their production databases.
Which of the following statements is true the data warehouse consists of data marts and operational data?The operational data are used as a source for the data warehouse. An operational system is used to run the business in real time and is based on current data.
|