Tag: Augmented Analytics Benefits

From Business Intelligence to Augmented Analytics: What and Why

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October 29, 2020

Augmented Analytics is the Next Generation of BI Tools for Business Users

As business intelligence solutions and BI Tools evolve into Augmented Analytics, business users can achieve valuable insight and take appropriate action to optimize resources and enable continuous improvement. As Gartner has predicted, the market is responding to business needs by transforming business intelligence tools into sophisticated Advanced Analytics that are easy-to-use. These augmented analytics solutions support the needs of the average business user, improve productivity and collaboration, and assure data democracy and Data Literacy across the organization.

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Augmented Analytics Makes Competition Easy!

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October 27, 2020

Augmented Analytics is the Secret Weapon for Competitive Advantage!

How do you compete? There are probably other businesses in the market that do what you do but your product or your services must stand out. How do you take all the data you collect on a daily basis and use that data to your advantage to point you in the right direction?

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DWH and Augmented Analytics Simplifies Info Management!

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October 20, 2020

Is the Idea of Data Warehouse and Data Analytics Overwhelming You?

If your business is struggling to manage big data and data from disparate sources, your team should focus on several key areas. First, you will want to review your datawarehouse (DWH) capabilities. If those capabilities are not cutting-edge, you should consider a review and re-engineering of this area of your infrastructure to be sure your growing data needs can be satisfied so that your team is not overwhelmed or swamped with information.

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What is Auto Insight? It Is Analytics Made Easy!

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September 21, 2020

Auto Insight Can Help Business Users Analyze Data at the Touch of a Button!

When you are trying to implement a data democratization initiative and give your business users access to analytics, you can run into roadblocks with analytical tools and solutions that are too difficult for the average skills of a business user. It is impossible to achieve your goals and ensure that every user is comfortable with data analytics and fact-based decision-making if you don’t give your users a tool that they can use as easily as they use Google or other familiar search mechanisms.

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Predictive Modeling Is Not the Sole Domain of Analysts!

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September 15, 2020

Assisted Predictive Modeling Lets Business Users Plan & Forecast with Confidence!

When businesses take on the task of forecasting and planning, it is important to provide the tools to go through this process at all levels with data integrated from the various systems and databases across the enterprise and to provide simple tools for all users that can be adopted and used to take on the various tasks and responsibilities involved in planning and accurate forecasting.

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White Paper: Digital Transformation Requires Commitment and Five Points of Integration

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August 11, 2020

download-whitepaper

Whether a business addresses or ignores the Digital Transformation movement, it is here to stay and Dx will change markets and competition. If a business truly wants to embrace Dx, it must be willing to take the necessary steps and engage in a review that touches all corners of the organization. To plan and execute a comprehensive, effective Digital Transformation (Dx) project, the business must consider five points of integration including Technology including Infrastructure, Software, Hardware, Network, Mobility, Enterprise Culture including Process and Analytics, Team Members, Suppliers, Partners, Vendors and Stakeholders, Customers.
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Digital Transformation Requires Commitment and Five Points of Integration

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August 4, 2020

Whether a business addresses or ignores the Digital Transformation movement, it is here to stay and Dx will change markets and competition. If a business truly wants to embrace Dx, it must be willing to take the necessary steps and engage in a review that touches all corners of the organization. To plan and execute a comprehensive, effective Digital Transformation (Dx) project, the business must consider five points of integration including Technology including Infrastructure, Software, Hardware, Network, Mobility, Enterprise Culture including Process and Analytics, Team Members, Suppliers, Partners, Vendors and Stakeholders, Customers.

Download the Whitepaper: Digital Transformation Requires Commitment and Five Points of Integration

Elegant MicroWeb (Smarten Self-Serve Data Preparation) is Named as a Representative Vendor in Gartner 2020 ‘Market Guide for Data Preparation Tools’, published July, 2020

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July 29, 2020

Elegant MicroWeb is pleased to announce that its Smarten Augmented Analytics solution is once again included as a Representative Vendor in the Gartner Market Guide for Data Preparation Tools, published July 9, 2020 (ID G00719343).

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Augmented Analytics and ETL Tools for Business Users!

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July 20, 2020

How Can Business Users Prepare Data and Perform Analytics?

Can Business Users Really Figure Out Data Prep and Analytics?

It is a great idea to get your business users involved in analytics and to encourage and build data literacy in your enterprise but one of the things that often stops an organization from implementing self-serve analytics is the need to gather and prepare the data for analytics. How can IT or data scientist staff turn over day-to-day analytics when data is spread across the enterprise and it is so difficult to integrate that data and prepare the data for analytics?

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Let’s Talk About Citizen Data Scientists!

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July 15, 2020

My Friend is Wrong! Citizen Data Scientists ARE Important!

Do You Want To Understand and Enable Citizen Data Scientists? You SHOULD!

I had a conversation with a dear friend the other day and one of the things we discussed was the ubiquitous mention of Citizen Data Scientists in technology and industry publications and conferences. My friend (who shall remain nameless), insisted that this was just another passing fancy and that Citizen Data Scientists were not really all that important in building the enterprise of the future.

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