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    Mitigating Data-Related Challenges with Cognitive Technology

    Grace Aglubat, VP, Information Technology, PHINMA

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    content-imageGrace Aglubat, VP, Information Technology, PHINMA

    Since the pandemic, the business landscape has been focusing on information security to protect its employees and client data from growing cyber threats. On the other hand, organizations also needed to gain actionable information on changing customer behavior to implement strategies that best align their internal operations with emerging market trends. The amount of unstructured data that companies started receiving also increased exponentially due to the rise in digital transformation, which led to the skyrocketing implementation of new technologies that can assist in fast-tracking process digitalization while safeguarding sensitive data.

    Leveraging Technological Advancements

    Today, it is critical that businesses have organized data or consolidated information about their customers to capture critical insights and develop ser vices or solutions that are relevant to both internal operations and external clients. In pursuit of this, firms began integrating cognitive computing into their business processes to leverage its ability to enhance data analytics competencies, customer interactions, and overall efficiencies of traditionally cumbersome tasks

    A prime example of this is the real estate space where cognitive analytics engines are used by property managers to assess the specifications and budgetary constraints of their prospective clients. The healthcare industry, on the other hand, takes advantage of cognitive computing to collate information, reports, and data from disparate sources, thereby boosting caregivers’ ability to better monitor and treat patients with best-suited care programs. Additionally, the emergence of cognitive computing-powered tele-consultation offerings is supporting physicians in seamlessly connecting with their patients regardless of their location and offering the most relevant treatment avenues.

    Importance of Data Security

    However, with the digitalization of business processes comes the challenge of keeping information and data safe, which is the core driver of the burgeoning emphasis on educating/ training employees.
    Currently, there are a plethora of mobile applications and other tech-driven solutions asking for information, which makes it critical for individuals to understand what type of information and data is collected. Especially with the increasing prominence of cyber threats, businesses should focus on ensuring that information security controls are in place and employees are aware of how to protect company information as well as their user data from cybercriminals. Apart from implementing technology solutions and digital platforms into the company, it is also important to evaluate the resulting changes newer deployments can cause on the cybersecurity measures safeguarding sensitive business information.

    “Firms Began Integrating Cognitive Computing Into Their Business Processes To Leverage Its Ability To Enhance Data Analytics Competencies, Customer Interactions, And Overall Efficiencies Of Traditionally Cumbersome Tasks”


    Despite the growing significance of dedicated cybersecurity and data management solutions, organizations often fail to make the most of their implementations due to a lack of user (employee) knowhow. Even the solutions geared to help employees be more efficient, effective, and productive may not reap the desired outcomes if users struggle to grasp the systems' capabilities. Concurrently, implementing new platforms or applications drive changes that cascade across the organization, which leads to unacceptable results. Therefore, employees must accept such transitions to gain a deeper understanding of the technologies, how they address prevalent issues and their overall lifecycle within an organization.
    Standardization of Cognitive Computing

    With its ability to provide the enhanced insights and security needed in the current cyber threat landscape, digital era businesses are driving the standardization of cognitive computing in cyber security and data analytics. Cognitive security provides deeper visibility into the purpose and behavior of both external and internal threats posing a danger to their computing infrastructure. Additionally, cognitive computing enables advanced threat intelligence that learns patterns of malicious behavior to support businesses in identifying, tracking, and preventing attacks.

    A majority of information security teams today use Big Data and analytics technologies to mine corporate data for security indications, which aid businesses in better understanding of their data and allow a faster reaction to security concerns. Combine cognitive computing into the mix, and firms are empowered to improve the usage of their vast datasets for better client engagements or stronger information security alike. Aside from these features, cognitive security technologies improve the user skillsets in charge of data protection, boosting both infrastructure and human capacities to solve cyber security concerns and incidents before they occur. Becoming more robust than it was a decade ago, cognitive computing is poised to provide technical advancements in healthcare, construction, housing, and other industry sectors over the upcoming years.
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