About

Oracle is a database management system designed for data warehousing and fulfilling enterprise’s grid computing requirements. For database interaction, it supports SQL (Structured Query Language). It is a cost-effective solution for data and application management which makes it the first choice for enterprises. Oracle database developers have various language choices when it comes to developing applications such as Java, C++, PL/SQL, Visual Basic, etc.

Application Management: Application management is defined as the lifecycle process for software applications. It includes how an application operates, upgrades and its version control. Application management services are an enterprise’s effort to govern and make sure that the applications are running optimally, efficiently, and effectively. This system is a service operation function that supports and manages stakeholders and applications.

Application Development: The process of creating a set of programs or a computer programs to perform various tasks as per business requirement is termed as application development. Applications help in the automation of business processes such as calculation of monthly expenses, scheduling sales reports, etc. Gathering requirements, designing prototypes, testing, integration, and implementation are the steps followed in app building.

Agile Transformation: Agile transformation refers to an act of transforming an organization’s nature or form into a flexible, dynamic, self-organizing, collaborative one. The values and principles of Agile manifesto not only apply to development teams but can be exercised and taught throughout the organization. To fully utilize the benefits of Agile transformation, the organization needs to understand its meaning and values to achieve true agility.

QA Testing: QA Testing or quality assurance testing is done to ensure that the products or services provided by your organization are of high quality. It helps in diagnosing any loopholes which when not sorted might create trouble for the users. It is used to prevent any issues which might create hindrance in delivering best products and services to the customers. An ideal QA Testing must be a combination of manual testing and automated testing.

API Management: API management is all about managing Application Programming Interfaces (APIs); it includes web interface creation, publication, access control, enforcement of usage policies, performance reporting, usage statistics collection and analysis and nurturing the subscriber community. The components of API management provide tools and mechanisms to support subscriber and developer community.

Application Modernization: Application modernization is the process of modernizing existing legal applications which includes their internal architecture, features, and platform infrastructure. These days, mostly the discussion regarding application modernization comprises of monolithic and on-premises applications. These are typically maintained and updated using waterfall development processes.

Cloud Services: Cloud services refer to those services which are delivered over the internet to the companies and customers on demand. There services are designed to provide affordable and easy access to resources and applications such that there is no requirement for hardware or internal infrastructure. Employees use cloud services daily in different forms for completing various tasks.

DevOps: DevOps which is a clipped compound of operations and development can be defined as a software engineering practice aiming at software operation and unifying software development. It strongly advocates the monitoring and automation at all the steps of integration, testing, software construction, infrastructure management, and releasing to deployment. It aims at increased deployment frequency, dependable releases and shorter development cycles closely aligned with business objectives.

Cloud Migration: Cloud migration is defined as the process of moving digital assets such as IT resources, workloads, data to the cloud infrastructure. In simple words, cloud migration means moving data and tools from old data center to the cloud. Under cloud migration, movement may be of all or limited assets. It is much wider term and includes much more than the movement of assets from one place to the other.

Infrastructure Support System: The infrastructure support system is crucial as it ensures that your on-premises hybrid IT environment and cloud are stable and deliver high performance. Infrastructure support services help in keeping the infrastructure reliable, proactively improved and highly available. This happens with setup, monitoring, optimization, administration, design consulting, cloud migration, and help desk services.

IaaS, PaaS, SaaS: IaaS is Infrastructure as a service, PaaS is Platform as a service and SaaS is Software as a service. SaaS is also known as cloud application services because they represent the generally used business options in the cloud market. PaaS or the cloud platform services are used for applications but also provide cloud components to certain software. IaaS is also known as the cloud infrastructure services as they are constructed of highly automated and scalable compute resources.

ServiceNow: Service now is known for processing and cataloguing customer service requests. It is a ticketing tool which is capable of raising requests consisting of problems, incidents, changes, etc. It has successfully become a cross-departmental platform which is known for functioning as an enterprise cloud solution. It possesses a great ability to create workflows which are known for automating the process of data extraction.

Data Strategy: Data strategy may be defined as a set of decisions which are known to chart a high-level course of action to achieve goals. This comprises of business-related plans which use the information to help enterprises reach their goals and for a competitive advantage. It provides an opportunity for improving, developing, and using the existing product line in a better manner. This strategy is driven by the organization’s holistic business model and strategy.

Data Insights: The knowledge that a company receives by analysing information related to a given topic is termed as data insights. The analysis of the data provides important insights which help business in making correct decisions thus reducing the risk factor. These insights vary to a great extent between industries, our ability to derive these insights depends upon a variety of factors. These factors include the problem which needs a solution, available of data quantity and the parameters of a given dataset.

Enterprise Data Management: EDM or enterprise data management refers to an organization’s ability to integrate, define and retrieve data both for the internal applications and external communication. It focuses on the creation of consistent, transparent, and accurate content at the same time emphasizing granularity, meaning, and data precision. It deals with the process of content integration into business applications and how it passes from one business process to the other.

Data Governance: Data governance at macro level relates to the political concept and forms a part of internet governance and international relations. At the micro-level, it deals with the concept of data management and forms a part of the corporate data governance. Data governance mainly focuses on data usability, availability, security, consistency, integrity and includes the establishment of process.

Analytics: Analytics refers to the systematic computational analysis the data or statistics which is used for the interpretation, communication and discovery of the data patterns. It helps in effective decision making with the application of data patterns. It is highly valuable in the areas which are rich with recorded information, it mainly relies on the simultaneous application of computer programming, statistics, and operations research.

Enterprise Architecture: Enterprise architecture can be referred to as a practice which is done for conducting enterprise analysis, planning, design, and implementation. All this takes place with the help of a comprehensive approach at all times which is required for the successful development and execution of strategy. Architecture principles and practices are applied under the enterprise architecture to guide organizations.

Business Architecture: Business architecture represents multidimensional business views of information, capabilities, organizational structure, and end-to-end delivery. It also represents the relationships among these views and products, initiatives, policies, strategies, and stakeholders. When applied, the business architecture is known for providing bridge between the enterprise strategy and enterprise business model on one side and business functionality on the other.

Solution Architecture: Solution architecture is a term which is used in IT which has many definitions. It is a description of a focused and discrete business activity or operation and how IS and IT supports the operation. In contrast to the enterprise architecture, it is known how it seeks to define a solution within the context of an initiative or project. It is a means to realise a technological strategy as it has a close association with actual projects and initiatives.

Engine: An engine may be defined as a program which performs an essential or core function for the other programs. These are used in subsystems, applications, and operating systems for coordinating the operations of other programs. It may be described as a special purpose program which utilizes deep learning algorithms to query data. It is designed in such a manner that its approach for finding the index may be changed to reflect new rules for not only finding but also matching the index.