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  • Writer's pictureJoe Knape

How to Securely Optimize Your Big Data Footprint

Nearly 50 percent of North American and European companies involved in "the 2018 State of IT" survey by Spiceworks said they hoped to increase their information technology (IT) budgets by 19 percent this year. They'll be allocating more money to software and hardware, including networking systems, cloud-based services, mobile technology, servers, external storage, and IT managed services.  Around 60 percent of the respondents expected their revenues to increase in tandem with their growing technology budgets. 

While increased digitization is critical to business growth and competitiveness, it comes with a vital legal responsibility—data compliance. As companies expand the diversity of the structured and unstructured data sets they're mining to analyze and produce actionable business intelligence, their data footprints grow. Like never before, these corporations are holding, transmitting, and processing massive customer data harvested from a wide range of digital assets, including:

  • Social media

  • Customer relationship management (CRM) systems

  • Phone call records

  • SMSs

  • Emails

  • Shopping carts

  • The Internet of Things (IoT) networks

  • Management information systems (MIS)

  • Mobile apps

  • Business websites

  • Electronic documents

Collecting, processing, and storing such huge amounts of data present unprecedented security and compliance challenges, especially in the wake of the recent General Data Protection Regulation (GDPR) updates. Two GDPR concerns that IT leaders and data controllers need to address are:

  1. Inadvertent disclosure: This is a breach of confidentiality case, whereby, private, personal data held by an organization ends up in the wrong hands by accident.

  2. Data loss: It implies the destruction or deletion of personal data beyond recovery.

Any corporation that fails to comply with GDPR provisions faces a fine of at least €20 million depending on its annual worldwide revenue. However, harnessing your growing data footprint does not have to expose your company to any run-ins with the EU. In any case, protecting customer data can also mean safeguarding actionable business intelligence that only you have.

Here are 2 practical strategies for data loss and inadvertent disclosure prevention:

1. Track and Classify Your Data

You cannot protect your data if you don't know what and where it is! Aided by data discovery and classification technologies, you can identify your data sources/silos to protect information based on how sensitive it is. You'll need to deploy complex arithmetic computing algorithms to access and identify massive, rapidly-growing, unstructured data sets from multiple independent sources. Likewise, analytical tools with capabilities for semantics and domain knowledge can help classify big data sets based on their sensitivity.

Common big data classification techniques include:

  • Decision tree

  • Support vector machine

You may identify and categorize your data based on several criteria, including:

  • Context: This could mean establishing a relationship between a category and the source software, the user who generated the data, or data silo.

  • Content inspection: It involves scrutinizing data to track common phrases (such as, "confidential") or expressions indicative of personal information (for example, social security and credit card numbers).

2. Figure Out What and When Data is at Risk

You may implement encryption and network-based safety measures for your data at rest. However, sharing data with customers, business partners, or suppliers poses a different level of threat. The same applies to data transmitted to user devices, such as desktops and smartphones. In most of these scenarios, the data is at the highest risk of loss at the time of access on endpoints. A robust data loss prevention plan should account for all data movement, and it must secure the most vulnerable transit points.

Discovering, classifying, and securing increasingly enormous volumes of structured and unstructured data from various autonomous sources surpass the processing capabilities of traditional database systems. With GDPR already in force, companies mining vast amounts of customer insights to drive business growth have no choice but to secure their data with the most advanced and effective loss prevention technology. At Infoedge, we have the tools to safeguard and optimize your ever-growing data footprint. Our cost-effective solutions can help deliver in-depth, timely analytics to inform your business growth strategy. Contact us now to learn more! 

#GDPR #Compliance #bigdata

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