A Solution to Data Capture and Data Processing Challenges

  • Source: CRM-ERP
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Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems.

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The Power of Cloud ERP on the Food Processing Plant Floor

For food processing companies, a comprehensive enterprise resource planning (ERP) solution offers a clear view of what is happening on the plant floor so they can track complete genealogies. Real-time data and flexible barcode functions enable efficiencies and productivity improvements. Download this white paper to learn more about the value of using a cloud/software-as-a-service (SaaS) ERP system on the food processing plant floor. Read More

On the Radar Splice Machine: Bringing Operational Distributed SQL Transaction Processing to Hadoop

  • Source: Ovum
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  • Published: January 15 2015
Online transaction processing relies on distributed data stores, and idustry segments such as digital marketing are generating an increased demand for transaction processing. Splice Machine is a new-generation online, distributed platform deployed on Hadoop. It draws on the scalability of an existing platform to leverage a rapidly growing skills base. So it can handle the high volume of processing required for interactive online transactions.

This product analysis reviews a transactional database that is competing in an emerging market for distributed online transaction processing, currently populated by NewSQL and NoSQL start-ups. Splice Machine is helping to transform Hadoop from an analytic to an operational platform. Read More

Reinventing Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud

Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside of production environments is crucial. Multiple copies of data and constant transmission of sensitive information stream back and forth across your organization. As information shifts between software development, testing, analysis, and reporting departments, a large "surface area of risk" is created. This area of risk increases even more when sensitive information is sent into public or hybrid clouds. Traditional data masking methods protect information, but don’t have the capability to respond to different application updates. Traditional masking also affects analysis as sensitive data isn’t usually used in these processes. This means that analytics are often performed with artificially generated data, which can yield inaccurate results.

In this white paper, read a comprehensive overview of Delphix Agile Masking, a new security solution that goes far beyond the limitations of traditional masking solutions. Learn how Delphix Agile Masking can reduce your organization’s surface area risk by 90%. By using patented data masking methods, Delphix Agile Masking secures data across all application lifecycle environments, providing a dynamic masking solution for production systems and persistent masking in non-production environments. Delphix’s Virtual Data Platform eliminates distribution challenges through their virtual data delivery system, meaning your data can be remotely synchronized, consolidated, and takes up less space overall. Read detailed scenarios on how Delphix Agile Data Masking can benefit your data security with end-to-end masking, selective masking, and dynamic masking.  Read More

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A Guide to Intelligent Data Auditing

  • Source: Tizor
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Data auditing is a form of data protection involving detailed monitoring of how stored enterprise data is accessed, and by whom. Data auditing can help companies capture activities that impact critical data assets, build a non-repudiable audit trail, and establish data forensics over time. Learn what you should look for in a data auditing solution—and use our checklist of product requirements to make the right decision. Read More

Optimizing Gross Margin over Continously Cleansed Data

Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally. Read More

Four Critical Success Factors to Cleansing Data

Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology. Read More
 
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