Data Strategy – Business Intelligence
Data Strategy A data strategy is defined as a set of choices and decisions that will guide and enable a high-level course of action to achieve high-level business goals. Data strategy has the following purposes: • Alignment with business and providing guiding principles • Data strategy defines the vision, mission, and goals of the data
Step to Create Data Strategy – Business Intelligence
Step to Create Data Strategy There is a ten-step process to create a data strategy document, as follows: 1. Build awareness: This is a first step that creates awareness of the issue and acknowledges the need to create an enterprise strategy and enterprise program. To do so, create awareness about the pain areas related to
Data and Analytics Approach and Strategy – Business Intelligence
Data and Analytics Approach and Strategy The strategy of an organization flows from business strategy to information strategy, which includes application and data strategy. It is essential that information strategy matches with business strategy. Information strategy consists of application strategy, data strategy, business intelligence strategy, and analytics strategy; all of these must align with the
Mappings – Business Intelligence
Mappings The purpose of this matrix is to align the focus of business strategy with data analytics strategy. Like all the programs, questions to be answered include, What is the value or value proposition for our customers in terms of providing data insights? What business process and response changes give these new insights? Figure 7-11
Step to Create Data Strategy 3 – Business Intelligence
7. Develop a roadmap: Create a roadmap based on any recommendations. This roadmap could range from three to five years. For example, you were advised to start and increase the maturity of analytics. This is done in two major steps. The first step is to enable access to historical data, tools, and skills for individuals
Step to Create Data Strategy 2 – Business Intelligence
6. Develop Recommendations: After developing vision and goals, the next steps are to provide recommendations based on the current state, and on the vision and goals for the future. The comprehensive solution and recommendations can be from people, process, and technology prospectives. Figure 7-12 demonstrates technical levers to govern data management, like data architecture, metadata,
Cloud security overview – its importance and challenges – Introduction to AWS Security Concepts and the Shared Responsibility Model
Cloud security overview – its importance and challenges As we embark on our journey into AWS security, it is essential to understand the broader landscape of cloud security. This section will set the stage by highlighting the importance of cloud security in our increasingly digital world and the unique challenges it presents. The significance of
Cloud security challenges – Introduction to AWS Security Concepts and the Shared Responsibility Model
Cloud security challenges Despite the numerous benefits of cloud computing, it also introduces a unique set of security challenges that organizations must address. These challenges stem from the inherent characteristics of the cloud, such as its shared, on-demand nature, and the fact that it often involves storing and processing sensitive data in third-party data centers.
Complexity – Introduction to AWS Security Concepts and the Shared Responsibility Model
Complexity Cloud environments offered by a leading provider such as AWS are inherently complex. This complexity is multifaceted, stemming from the vast array of services offered, the dynamic and scalable nature of the cloud, and the global reach of the cloud platform. AWS offers well over 200 fully featured services from data centers globally. These
Visibility and control – Introduction to AWS Security Concepts and the Shared Responsibility Model
Visibility and control In the realm of cloud security, visibility and control are critical aspects. Unlike traditional on-premises environments where infrastructure is physically accessible and operations are often static, the cloud introduces a dynamic, scalable, and distributed environment that necessitates a different approach to maintaining visibility and control. Visibility in the cloud is about having
