Question One: Identify and formulate a research problem from the articles in your selected topic.

Question Two: Use the template provided and write a literature review,

Topic $2$: Collaborative business intelligence This topic focuses on collaborative BI or social BI which involves the merging of traditional BI with collaboration tools such as social media and web technologies. It allows the easy sharing of reports as well as increased engagement between stakeholders and subject matter experts to make better business decisions.

Article $1$: To enable efficient decision$-$making, professionals need to collaborate with individuals with data being collected from various sources like distributed clouds for storage, very large databases and social media. Authentication and validation are needed for access to the relevant roles. There are further applications of machine learning to deal with unlawful actions. This paper proposes a Context Aware Secure Collaborative Business Intelligence Framework $($CASCBF$)$ to address the same. CASCBF is divided into three layers. Multiple sources of data provide different levels of abstraction and granularity of access control to different roles. To control different types of assemblage of data resources from distributed sources and provide right access to users to the edge of the network is a core challenge.

Article $2$: Cooperative work in the processes of analysis and decision support currently gains strong attention in the business world. This is motivated by spreading corporate structures and technical developments like social media and network$-$ oriented data storage that encourage the users$$ comprehension and demand for easy communication about data. This article reflects the state of research in the domain of BI regarding the opening of processes for new data sources and analysts. Existing approaches are often labelled collaborative business intelligence $($CBI$)$ but are highly different in definitions and focus. Therefore, a framework is presented and three main fields for the research of CBI are identified. They encompass internal communication, data storage with $($external$)$ partners and data analysis with partners. This article compares the findings with developments on the software market and describes open topics in the research domain.

Article $3$: Industry leaders believe that Artificial Intelligence $($AI$)$ can help solve any business problem with the right amount of data to learn from and smart algorithms to implement AI$.$ The magic bullet of AI will get the business stagnation out of the door, help solve your back$-$office issues, skyrocket your customer engagement, and stand up to new business models with the least amount of intervention from users. Beyond the hype of AI$,$ beating human opponents with possibly every sort of board game and game show, composing music, robot only soccer matches or impending AI apocalypse, there is a gap between industry expectations from AI that can solve anything vs more realistic applications of AI that can attack the problems enterprises are facing $$NOW$.$ Organisations need to shift the conversation from being too late to adopt AI technologies to business outcomes AI can enable with its current maturity. The root cause of this problem is primarily due to the obfuscation of AI capabilities and the lack of understanding of how AI works. Business Analysis $($BA$)$ professionals with the capabilities to understand business, technology, and customers have the first$-$mover advantage in unpacking AI and providing real$-$ world applications of AI with immediate practical use. The approach for getting the BA professionals up to speed with AI should start with: $$ Clearing the assumptions around types of AI technologies, industry terms, implementation approaches, current capabilities, and limitations$.$ Understanding where the field is going, so that they can understand and adapt to changes as required to be effective in a project where AI is the key technology being used; and, Appreciating changing best practices, methodologies, and tools to apply in business analysis for AI$.$

Research Problem Example: Our company currently struggles to access and analyze all our data scattered across different systems. This makes it difficult to understand sales trends, customer behavior, and overall performance. We need a cloud$-$based business intelligence $($BI$)$ solution that gathers data easily, provides clear reports and dashboards, and helps us make data$-$driven decisions.