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5 Requirements for Effective Self-Service Data Preparation

  • 5 Requirements for Effective Self-Service Data Preparation-

    Data Masking

    Data discovery tools provide tremendous business value, but they can also pose significant risks if data isn’t handled in the right way. While this technology can help users build and share information, many times the information contains unprotected personally identifiable data (e.g., Social Security numbers), sensitive personal data (e.g., medical records and procedures) and commercially sensitive data. Internal employees are the most common cause of data breaches, and data loss can result in customer and revenue loss, compliance fines, legal action and brand damage.

    Data masking functionality enables analysts to easily and reliably remove or obscure confidential data with intuitive redaction capabilities without impacting its value in the analytics process. Using this feature, analysts can access, analyze and share critical data, even in heavily regulated industries like health care and financial services, without compromising customer and employee privacy.

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5 Requirements for Effective Self-Service Data Preparation

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  • 5 Requirements for Effective Self-Service Data Preparation-3

    Data Masking

    Data discovery tools provide tremendous business value, but they can also pose significant risks if data isn’t handled in the right way. While this technology can help users build and share information, many times the information contains unprotected personally identifiable data (e.g., Social Security numbers), sensitive personal data (e.g., medical records and procedures) and commercially sensitive data. Internal employees are the most common cause of data breaches, and data loss can result in customer and revenue loss, compliance fines, legal action and brand damage.

    Data masking functionality enables analysts to easily and reliably remove or obscure confidential data with intuitive redaction capabilities without impacting its value in the analytics process. Using this feature, analysts can access, analyze and share critical data, even in heavily regulated industries like health care and financial services, without compromising customer and employee privacy.

Business Intelligence (BI) and Big Data analytics tools have fundamentally transformed the way organizations operate. Business leaders across industries now use Big Data analytics technology for a wide range of processes, objectives and management needs. And the potential applications of modern BI tools are practically endless, as virtually every aspect of operational management and strategic oversight can benefit from more powerful and rapid insights.

But while the technology is there, studies have shown that return on investment (ROI) has been elusive at best for the vast majority of adopters. In fact, business analysts claim that 80 percent of their time is spent preparing data for analysis, and they still never seem to have the information they need.

Self-service data preparation (prep) is a critical, yet often overlooked, factor in the analytics process. In this slideshow, Datawatch Corp, has identified five essential self-service data prep capabilities every analyst must be able to access to derive maximum value from analytics solutions and help their organizations make more meaningful and timely decisions.