• Data compliance and personal information protection regulations are constantly evolving, making it a full-time job to keep up with them.
• Vendors’ adherence to the most up-to-date data standards and practices is an absolute yes regarding CCPA compliance.

Poorly designed display solutions are more undoubtedly destructive to B2B enterprises than beneficial. Even though a zero-tolerance policy is necessary for safe contextual placement, there are numerous aspects to consider when choosing the right platform for your business.

From the quality of the core outputs to the quality of the data connections and the quality of the reporting suite – these elements play a huge role in the smooth sailing of the business.

However, even the most basic brand protection measures aren’t enough for savvy advertising and media purchasers when a business’s reputation is at stake. The answer is simple: brand safety must be included from the start.

Data compliance and personal information protection regulations are constantly evolving, making it a full-time job to keep up with them. B2B marketers, no matter how hard they try, will always have more questions than answers.

If you don’t take precautions to safeguard your business’s reputation, your organization could face the following risks:

FINANCIAL RISK:

• Fraud
• Fines

REPUTATIONAL RISK:

• Content presentation
• User experience

LEGAL RISK:

• Privacy
• Terms and Conditions
• Data protection

Locating trustworthy and well-informed Vendor Partners that can contribute to the security of your business and its consumers is of the utmost importance.

To facilitate the verification process for B2B marketers, we have compiled this checklist. Bringing openness and responsibility to the vendor selection process will enable you to make the best decision for your company.

COMPLIANCE

Vendors’ adherence to the most up-to-date data standards and practices is an absolute yes regarding California Consumer Privacy Act (CCPA compliance). The best way to ensure that everyone connected to your organization is safe is by asking these and more questions to get everything verified.

• To what extent does the provider meet the requirements of the General Data Protection Regulation?
• Is the provider of the service Privacy Shield Certified?

Can the supplier produce a Certificate of Insurance proving the following coverage:

• The commercial general liability?
• Responsible conduct in the workplace?
• Cybersecurity?
• Liability for data security?
• Compensation for employees?
• Responsibility of employers?

DATA PROTECTION and PRIVACY

DATA COLLECTION

Your information is worth a lot of money to companies. Even if they ask kindly, not every vendor can be trusted with your confidential information if they can’t confidently answer the following questions.

• Has the method to gather information by the vendor shared with you?
• Do they use encryption on all data they store?
• Can you fill out a secure form (HTTPS forms) on the vendor’s website?
• Does the vendor fix the Top 10 vulnerabilities identified by the Open Web Application Security Project (OWASP)?
• Can you send and receive files securely using SFTP and HTTPS with this provider?
• If they have data retention policies, how long do they keep them?
• After the retention term has ended, how does the vendor ensure that the data is deleted permanently and securely?
• Does the service provider encrypt personally identifiable information (Pii) both while stored and while being transferred?
• To what extent are systems and applications protected by the current infrastructure?

DATA ACCESS

It is just as critical to know who has access to your data as to understand how they have gained access. For legal and ethical reasons, businesses should limit access to private information to only the most essential employees and teams.

• Can you verify that the vendor offers encrypted activity logs, employee onboarding, and exit access management?
• Does the vendor restrict information access to only those with a genuine “need to know”?
• Is there a system in place to get the word out to workers about the policies and procedures they need to know to keep their personal data safe?
• Does the provider follow a documented procedure to keep information secure from theft, misuse, and other forms of loss?
• Does the provider mandate that all staff members use complex passwords to access its systems?
• Does the service provider mandate (in writing) that all employees with access to Personally Identifiable Information use complex passwords (as per best practices)?
• Does the vendor mandate that all users with sensitive data access change their passwords at least once in 90 days?
• Does your provider have an established and written Information Security Incident Response Policy? Perhaps, a ISIR Team or Incident Response Group for Security?
• Does the vendor do a criminal record check on all workers who may have access to your data or other sensitive information?

TRANSPARENCY

Does your supplier solemnly pledge to provide you with 100% accurate information? Trust in a company’s reliability, and legitimacy is crucial. You need to carefully design more questions to ensure that the vendor is worthy of your trust.

Last but not least, you need to ask some tough questions to segregate the pretenders from the real contenders.

To summarize,

A significant amount of responsibility is attached to the task of protecting the personal information of your customers, workers, and everyone in between. Your ideal Vendor Partner will be responsive to your needs, honest with you, and (most likely) come well recommended by others. You will be able to make an informed judgment about a brand’s safety if you are armed with our Brand Safety Checklist. This decision will be based on your own trust and verification.

Click Here to get more useful information about Brand Safety Guidelines by reading our Whitepaper.

• A company at a higher stage of the data maturity model can integrate data analysis into business practices.
• Beyond maximizing financial results for the firm, the ability of accelerators to minimize waste has a significant social, environmental, and cultural impact.

Have you ever wondered what fuels the digital world? You got it right; it’s data! But how do companies hunt for new data?

Organizations are generating more data in new and different ways, including the proliferation of edge and IoT devices through new app monitoring and observability streams and the increasing data generated from new digital services and experiences.

Firms are mandated to leverage their wealth of data that can benefit their business than allowing it to become an untapped resource.

But how can organizations build mature data innovation practices that can help them unlock the value of data? The multi-faceted process calls for a comprehensive look at high-quality data and technologies that can help scale and keep pace with vast and accelerating data generation.

Additionally, it requires cross-functional collaboration between technology teams like data scientists, developers, and analytics teams to support the organization’s “data disruptors” effectively.

Segmenting the Market in Terms of Data Innovation Maturity

Some of the important questions that can help gauge the maturity of the data are:

• How thoroughly they integrate their data.
• How well their statistics are gathered (i.e., their accuracy and quality).
• The effectiveness of IT and data users’ cooperation throughout project lifecycles.
• The use of technologies like machine learning and artificial intelligence to support, scale, and automate data management processes.

Typically, there are three stages of data innovation maturity. Understanding the data maturity stages allows companies to execute the development of data usage. Here are three common stages of a data maturity model:

Level 1: This is the initial stage where a company is in the process of putting a data strategy in place. Rather than sourcing data from online and external sources, it relies on internal data – from surveys and other data measuring tools.

Most enterprises at this stage struggle with a fragmented view of their imperfect data and are also prone to data loss, hacks, and major disruptions. Neither is there any data classification or data backup. To mount it all, there’s no action plan for disaster recovery and data restoration in case of major data loss.

Level 2: This is the stage where organizations get a clear understanding of the importance of data and how it can enhance business operations. At this point, enterprises are in the process of adopting data into their decision-making process. Results of the business and progress are analyzed by employees using data. Because this calls for increased use of data, appropriate security measures and automation processes are in place to maintain data flow.

Level 3: This is the advanced stage of data maturity that calls for analyzing data usage from earlier stages and using the knowledge derived to compete in the marketplace. Companies at this stage have a user-friendly process to access data and promote data literacy.

Most organizations fall into Level 1, with fragmented and inefficient data management practices. With a fragmented view of their imperfect data, most organizations struggle and lack the technologies to keep pace with their data and are grappling with infighting among teams. At the same time, just 16% of organizations meet the threshold of operating an Accelerated Data Innovation practice. It is imperative that organizations radically evolve how they approach data management today to maximize the return on their data capital.

How to use data maturity models?

Professionals use data maturity models to determine their company’s data management practices. This helps them set goals and how their company can advance to the next level. A company at a higher stage of the data maturity model can integrate data analysis into business practices. This results in effective and data-driven choices.

Quantifying the Impact of Accelerated Data Innovation

Effective data management and analytics lead to better insights and positively impacts revenue. The benefits are, in fact, multi-faceted. Organizations operating in this environment have more data at their disposal. Organizations also witness positive changes in their data management practices, such as improved product or service quality, enhanced IT/application availability/predictability, superior customer service/experience, increased employee efficiency/productivity, and reduced organizational risk. Let’s take a look at some of the benefits:

Fuels decision-making: With data maturity models, organizations clearly understand how their employees are incorporating data into the decision-making process. Professionals can make informed decisions with data. For instance, when professionals at the management level start interpreting data, the information derived can be used to support the top performers in their company and guide the low performers toward better productivity.

Customer satisfaction: With their ability to interpret, understand, and react to market demands, data innovation accelerators fuel innovation. Organizations can maximize customer experience. Today’s organizations are focusing heavily on customer outcomes. Efficient data management practices that support innovation, differentiation, and higher customer satisfaction can significantly contribute toward this end.

Increased productivity:  Yet another way by which data management practice can drive value for an organization is by providing improved insight into employee productivity. Organizations can use the data from employees’ everyday work to identify loopholes that impact productivity and engagement. Employees, too, benefit as they can get key insights into key areas of improvement.

Deliver innovative offerings: The insights offered by data can be used for the purpose of innovation. Better data analysis can help organizations uncover opportunities within the market and help them gauge and adjust to changing customer preferences. This will help them cut competition and fulfil needs in real-time.

Maximizes app availability: With organizations using modern applications and increasing the use of microservices, containers, and Kubernetes, the amount and types of data produced by applications, too, changes. This can result in application monitoring and observability challenges. Organizations must increasingly apply advanced data management and analytics capabilities to effectively measure performance, availability, and user experience.

Conclusion

It’s become a necessity for almost every organization to use data for digital transformation. Besides, they also need to manage the data well so as to drive differentiation to drive measurable value. Unlocking the true value can deliver results and empower their journey towards innovation.

Data Innovation Maturity provides an edge. Firms having high data innovation maturity are confident that they have the technical expertise required to adapt and thrive through disruptions. With the business climate becoming more challenging, businesses must truly identify the potential of data that that can make a true difference.

We may not realize it, but technology is indeed helping us stay healthy. A smartwatch tracks your heart rate, step count, blood oxygen level, and calls for help if there are any health issues. Doctors are also using medical devices to keep track of their patients. Doctors can track patient’s electrocardiographic signals, blood pressure, and oxygen saturation all via telemonitoring.

As the population is rising, so does patient data. There comes the need for data centers to manage a humongous amount of healthcare data.

Driven by generous incentives to adopt electronic medical record (EMR) solutions and increased documentation, healthcare providers are now facing issues with managing, collecting, securing, and storing a generous amount of sensitive protected health information (PHI).

Implementation of best practices

As the healthcare industry enters a new decade, it undergoes a massive technological transformation. Running a data center is a complex task as it is important to maintain massive data along with security. Therefore, it is essential to implement best practices for healthcare data centers.

Following are the best practices one should follow to maintain healthcare data centers:

1. Unifying the data center with stakeholders and representatives

Healthcare is a sector where several practitioners and disciplines are brought together for a most noble cause, i.e., saving lives and improving patients’ quality of life. This makes sense to work with diverse teams by including representatives of all involved areas during the initial data center refresh phase.

Although teams may differ among organizations, it is important to consider stakeholders’ detailed knowledge about security, IT infrastructure, and applications.

New collaborative care models need better data integration and communication among healthcare providers so that patient data could be shared, aggregated, and evaluated by each stakeholder in the care continuum (including patients).

Clinical section representatives could offer valuable insights into how doctors, technicians, and nurses use resources. The team will also benefit from non-clinical users such as human resources, administrative services staff, and other facilities. Don’t forget to include a C-level sponsor to overcome barriers.

2. Describe your healthcare infrastructure strategy

The primary task is to assess your present data center. The Updated Configuration Management Database (CMDB) could play a powerful tool in gauging hardware and software assets of the current healthcare infrastructure.

The cross-functional team could come into play by helping the IT team go through CMDB findings to manage unused applications, devices, or hardware. Further, this best practice in healthcare for maintaining data centers will enhance security by eradicating vulnerabilities living in outdated systems. Also, it will help the cross-functional team differentiate between applications that are good candidates for modernization, which could be used to map interdependencies and data sources.

CMDB results will help your team align applications with optimal cloud and data center platforms.

3. Use of DCIM tools

Few things are important for data center operations best practices, such as an efficient data center infrastructure management (DCIM) platform. Managing a data center without DCIM software is like trying to drive a car without a clutch. With the help of DCIM tools, healthcare data center professionals could monitor power usage, traffic demands, and cooling needs in real-time.

4. Applying enhanced security to healthcare data center

To prevent data breaches, it is necessary to have robust security systems at endpoints such as mobile devices, smartphones, and tablets. For instance, a violation at Oregon Health and Science University included illegal storage of unencrypted patient data in the cloud by two residents. Therefore, security is a must.

5. Practice good data hygiene

By implementing good data hygiene in the healthcare sector, data centers could help patients and team members manage redundant, obsolete, and trivial (ROT) data and free up valuable storage and computing resources for more important requirements.

Reducing the burden on healthcare infrastructure could have a beneficial impact on data center standards. This is because computing equipment will have lower power and cooling demands.

The Healthcare industry is expanding rapidly and raises questions about how to best maintain their data centers—in the cloud or on-premises.

It is important to conduct a detailed data center evaluation when making changes in the healthcare IT infrastructure. Whether supporting mobile devices and internet-of-things (IoT), refreshing hardware, integrating cloud-based applications, and deploying new software, you must evaluate the healthcare IT infrastructure changes.

What services are included in a healthcare data center?

Following are the healthcare data center services:

• Dedicated data centers
• Private suites
• Secure cages
• Individual cabinets
• Carrier-neutral network
• Multi-homed BGP-based managed internet access
• 24-hour smart hands
• Data center asset tracking

Final words

It is amazing to see what technological advancements can do for humans. Data centers are the heart of many healthcare IT accomplishments. Life sciences companies and healthcare innovators are concentrating on developing diagnostic technologies and digital medication strategies to boost 2021 best practices for healthcare data centers.

For more information download our latest whitepapers on data centers and best practices.