Question

Search the Internet for data analytic tools and review tools for business use. Consider key features, usefulness, and cost.

Respond to the following in a minimum of 175 words:

• What criteria do you think are important in the selection of a data analytic tool?
• How could data analytic tools help small businesses?
• How might your selection criteria be different for a medium or large business?  

Answer 1

`Hey,

Note: Brother if you have any queries related the answer please do comment. I would be very happy to resolve all your queries.

1)

1. Research and discovery

First, business professionals must determine the current state of analytical tool implementation and analytical capabilities within their organization. To do so, they must conduct in-depth interviews with key stakeholders including business intelligence developers, administrators, and IT executives, said Levy. Essentially, you must interview the people that are going to both use and benefit from analytical tools, he added.

"That helps us to understand what the ins and outs are around who's using these things, what they are using, what tools they use to do their work, what the tools can do, what they can't do, and if they are being used correctly," said Levy. "Are these tools being used to their fullest capabilities? Do they have the in-house knowledge required to make the fullest use of their portfolio of software?"

2. Current state landscape

The second step involves taking inventory of market's current analytical tools and separating them into different classes. These tool classes include report writers, semantic layer reporting tools, MDX/Cube query tools, data discovery and visualization tools, embedded BI and reporting tools, data science and modeling tools, as well as AI and machine learning use case driven tools.

"Where is the next wave going? What's the landscape like in terms of the various vendors and the tools that they offer?" Levy said. "You start to sift those into the different holes that you found in the first step."

2)

Data analytics simply involve using the data a business already has to help it make better business decisions. Sure, it can be expensive to hire a specialist with a background in programming, data ­science and business ­processes. But small ­businesses in particular can start with basic analytics without spending much money at all.

For most small businesses, the place to start is with the software already in place. If the business has been delaying an upgrade to its accounting or customer relationship management tools, this might be a good reason to go ahead; the most recent versions of every tool have more reports and analysis tools built in.

3)

A few potential criteria. The starred ones are those that are important to me:

1. Is it a new product / company, or well established?
2. Open source? Or free trial available?
3. Price (*)
4. Can work with big data (*)
5. Compatible with other products
6. Ease of use, GUI offered (*)
7. Can work in batch / programmable mode (*)
8. Offers an API
9. Capability to fetch data on the Internet, or from database (SQL supported)
10. Nice graphic capabilities (to visualize decision trees, for instance) (*)
11. Speed of computations, efficiency in the way memory is used (*)
12. Good technical support, training/documentation available (*)

Kindly revert for any queries

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