Critical Perspective Of Information Assignment Sample

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Introduction of Critical Perspective Of Information Assignment 

Slide 1: Title

Slide 2: Lay perspectives on big data: Insights from citizen conferences in Germany

  1. Three conferences were held between the people of Germany about the progress of big data
  2. There is the considerable worry that the interests of the people of Germany are not adequately considered as big data influences even more parts of the daily life of the people of Germany
  3. A new area called participatory assessment of technology which is also known as PTA is attempting to make these procedures fairer by including the voices of non-experts

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Speaker notes

As big data touches more and more aspects of the everyday lives of German citizens, there is a great deal of concern that their interests are not being fully addressed.

Slide 3: Lay perspectives on big data: Insights from citizen conferences in Germany

  1. When the participatory assessment of technology was first conceived, it was in response to a variety of issues raised by self-reflexive modernism as well as the dangers it brought
  2. Citizens' participation in the process of making of policy was specifically designed to question the authority of experts as well as make technological laws more participatory
  3. Worried about the durability of information, people of Germany requested privacy protection of metadata, particularly when it came to their patient data
  4. The citizens of Germany are concerned with the security of data

Speaker notes

Making technical laws more democratic by including the general public in policymaking is one of the main goals of involving citizens of Germany in policymaking (Jagadish, 2015).

Slide 4: Big data analytics

  1. Massive datasets that would be difficult to examine are being analyzed using the process of analytics of the big data
  2. The analytics of big data may help an organization to make good changes in the company, such as upgrading current offerings as well as boosting income per client
  3. Many assumptions may be eliminated with the use of analytics of big data, like which content to use, which approach of marketing to implement, which goods to create, among others
  4. All data analytics offers customers a complete picture of the consumer, which significantly reduces the amount of effort as well as time required from the employees

Speaker notes

Analyzing large amounts of data may remove a lot of assumptions, about which content to employ, which marketing strategy to adopt, and what products to build (Jinaet al, 2015). There are several benefits for businesses that use data analytics, including a reduction in the effort and time needed by workers.

Slide 5: How the marketing strategy got influenced due to artificial intelligence

  1. The clients will get customized communications at the right time in the life cycle of the buyer due to AI
  2. Marketers may also use artificial intelligence to detect the client's risk as well as re-engage them with relevant content
  3. Data science is very important for a business to make the proper marketing strategy
  4. In marketing, data science can be used in a variety of ways such as optimization of channels, segmentation of the customer, improved lead scoring as well as lead targeting, interactions in real-time and so on
  5. Data science provides valuable input to the behavior as well as pReferences of the customer

Speaker notes

Data science may be used in a range of methods in marketing, including lead targeting as well as scoring, channel optimization, consumer segmentation, real-time interactions, etc. Data science contributes significantly to the process of understanding consumer behavior and preferences (Jordan et al, 2015).

Slide 6: Reference list

Jagadish, H. V. (2015). “Big Data and Science: Myths and Reality”. Big Data Research, Vol 2, pages 49–52.

Jina, X., Waha, W. B., Chenga, X. ,Wanga, Y. (2015). “Significance and Challenges of Big Data Research”. Big Data Research; Vol 2 (2015) Pages 59–64.

Jordan, M. I and Mitchell, T.M. (2015). “Machine Learning: Trends, perspectives, and prospects”, Science, Volume 349, Issue 6245, Pages 255-260.

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