Single Version Of Truth Research Articles

Modern approaches to data storage: comparison of relational and cloud data warehouses using etl and elt methods

The paper analyses various aspects of the use of relational and cloud data warehouses as well as methods of integrating ETL and ELT data. A comparative analysis of these approaches, their advantages and disadvantages are provided. A central relational data warehouse is proposed that provides a single version of truth (SVOT), which allows standardising and structuring data, avoiding differences and providing the access to the same information for all users of an organisation. It is analysed the methodological approaches to implementing a data warehouse: top-down, bottom-up, and from middle. It is described cloud data warehouses that use cloud technologies to provide scalability, availability and fault tolerance, which is important for the companies with huge amounts of data. The advantages and disadvantages of ETL and ELT are analysed: ETL transforms data before it is loaded into the warehouse, which makes it easier to maintain data confidentiality. ELT performs transformation after loading, which allows for more flexible data processing directly in the warehouse. In the article, we deal with the approaches to implementing a data warehouse: top-down is suitable for strategic planning, bottom-up allows for faster results, and the middle approach combines both methods to achieve optimal efficiency. We considered cloud data storage: compared to relational storage, cloud storage is more flexible, scalable and efficient, providing speed and reducing infrastructure costs. It is described cloud storage architectures: massive parallel processing, hybrid architectures, lambda architectures, and multi-structured architectures. They provide high performance and flexibility in data processing. It is described data storage technologies: Data Lake, Polyglot Persistence, Apache Iceberg, Apache Parquet, and columnar databases that provide efficient storage and processing of large amounts of data

An Intelligent Approach of e-Repository Information for Central Citizen to Augment the Government Service by Crafting a Community Management Framework

E-Government initiative is one of the prime trends that have been opted by most of the government of the countries that comprises of various aspects and motives of serving the country people. This is comparatively a new field of research that concerns with the quality of services offered and processes to accomplish the services offered by the government. However, establishment of complete connectivity, co-ordination and collaboration between various ministries and departments is one of the key issues of this initiative that requires an interoperable multidimensional database with a centralized citizen information repository compatible with one another. This will not only integrate information from various sources and build a single point of contact with single version of truth to augment the government services but also will enhance the data visualization providing better insights of data and analytics with the introduction of data warehousing and business intelligence concepts.

A Model of Data Warehousing Process Maturity

Even though data warehousing (DW) requires huge investments, the data warehouse market is experiencing incredible growth. However, a large number of DW initiatives end up as failures. In this paper, we argue that the maturity of a data warehousing process (DWP) could significantly mitigate such large-scale failures and ensure the delivery of consistent, high quality, “single-version of truth” data in a timely manner. However, unlike software development, the assessment of DWP maturity has not yet been tackled in a systematic way. In light of the critical importance of data as a corporate resource, we believe that the need for a maturity model for DWP could not be greater. In this paper, we describe the design and development of a five-level DWP maturity model (DWP-M) over a period of three years. A unique aspect of this model is that it covers processes in both data warehouse development and operations. Over 20 key DW executives from 13 different corporations were involved in the model development process. The final model was evaluated by a panel of experts; the results strongly validate the functionality, productivity, and usability of the model. We present the initial and final DWP-M model versions, along with illustrations of several key process areas at different levels of maturity.

Challenges and conflicts integrating heterogeneous data warehouses in virtual organisations

This paper addresses challenges, which appear when heterogeneous data warehouses are integrated. Such a scenario especially shows up in the environment of virtual organisations. The involved companies, of the before named constellation, need to combine their business data to attain 'one single version of truth' for decisions beyond organisational borders. The occurring issues are depicted and analysed from an exemplary and theoretical point of view. Not only weaknesses, but also reasons for those shortcomings are analysed. The introduction throws a glance at growing data volumes and the derived consequences for the business. Afterwards, a working definition of the term 'virtual organisation' is established and the link and interdependence to information technology is offered. In the following sections schema and mapping conflicts are discussed. The eighth section targets the detection of organisational deficits, which are probably a facilitator for those problems. Moreover, path breaking decisions within a data warehouse integration project are visualised, to provide decision makers with some rough reference points. The paper is completed by a view on the human component and an outlook on in-memory computing.