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Discussion Question #1
How do you describe the importance of data in analytics?
Analyzing raw data and drawing inferences is what data analytics is all about. Analytical
procedures and processes have been mechanized into mechanical processes that process raw data
for human use. Data analytics may be used to improve a company's efficiency. Companies need
good data to define baselines, benchmarks, and targets to keep going ahead. Using data, you
would be able to define performance benchmarks, establish baselines, and develop performance
targets. Data may help you explain your positive and bad actions to your stakeholders. It doesn't
matter how horrible things end out. As much as you have credible proof to support your
judgments and methods, you have done your best. Use data to secure the well-being of your
customers. First and foremost, organizations should utilize data to enhance quality.
Can we think of analytics without data? Explain.
No, we cannot think of analytics without data. Using its straightforward facts and figures, we
may establish a starting point and set a goal. As long as we don't have the necessary data, it's
impossible to use analytics to achieve a goal, which is why we need it. A strategy is useless if
there is no data to support it. You may think about facts, figures, and insights similarly to an old
painting. Many dots, smears and marks in an abstract painting would be difficult to see from a
proximity of one foot or less. While it's simple to think of these paragraphs as your data, taking
them all together does not provide much information.
Discussion Question #2
Considering the new and broad definition of business analytics, what are the main inputs
and outputs to the analytics continuum?

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Inputs are converted into data and saved in the database. This is followed by analytic efforts to
generate and test knowledge used by users and apps. This method aims to deepen knowledge of
people and goods and improve foresight for a corporation. Today's big data may be organized or
unstructured, in smaller or bigger chunks, and in various ways. When it comes to making sense
of complex business operations, the current version of Big data is incredibly beneficial. Inputs
include corporate processes, the rise of social media, machines and the internet of things,
according to the paradigm "A Data to Information Continuum" in chapter two of the textbook.
Inputs are converted into data and saved in the database. This is followed by analytic efforts to
generate and test knowledge used by users and apps.
Prescriptive analytics explains how to proceed. Advanced analytics may provide real economic
benefit by utilizing Big data, boosting decision-making, and uncovering rare insights. Business
analytics helps companies understand people and goods and enhance foresight. Businesses might
derive significant results from complex data acquired.
Discussion Question #3
Where do the data for business analytics come from? What are the sources and the nature
of those incoming data?
The business model for business analytics is built using data from three different sources. It
relies on data from annual reports, profitability statements, marketing research, etc. An extensive
database is used to store numerous computer files and data that have been collected via the
application of statistical analysis.
Analytical data originates from the record of transactions and events inside a company. Users
may also contribute to the creation of data via enterprise applications and activities. Businesses

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Discussion Question #1 How do you describe the importance of data in analytics? Analyzing raw data and drawing inferences is what data analytics is all about. Analytical procedures and processes have been mechanized into mechanical processes that process raw data for human use. Data analytics may be used to improve a company's efficiency. Companies need good data to define baselines, benchmarks, and targets to keep going ahead. Using data, you would be able to define performance benchmarks, establish baselines, and develop performance targets. Data may help you explain your positive and bad actions to your stakeholders. It doesn't matter how horrible things end out. As much as you have credible proof to support your judgments and methods, you have done your best. Use data to secure the well-being of your customers. First and foremost, organizations should utilize data to enhance quality. Can we think of analytics without data? Explain. No, we cannot think of analytics without data. Using its straightforward facts and figures, we may establish a starting point and set a goal. As long as we don't have the necessary data, it's impossible to use analytics to achieve a goal, which is wh ...
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