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How Companies Can Leverage Their Existing Data Assets To Unlock New Business Opportunities?

Have you already heard about the latest update about Facebook who wants to play Cupid? At their F8 developer conference, the social network announced its entry into the online dating service. Why not? As Facebook users were able to reveal their relationship status since February 2004, with the existing user data form the ideal source it’s possible to find the perfect partner with the help of a suitable algorithm. However, this operation requires valid and high-quality data. At the same time, this announcement is a very good example of how companies can leverage their existing data assets to unlock new business opportunities.

 

Business can generally succeed in improving their own data quality by improving their data governance processes and the developing suitable strategies for complete data management. First of all, it is important to define the criteria for good data, which may vary depending on the company’s activity. These include aspects such as relevance, accuracy and consistency – in this case, data from different sources should not contradict each other. It’s also helpful to investigate where errors in master data are particularly likely to creep. Because here too the well-known programming wisdom applies: garbage in, garbage out. Poor data sources lead to poor results.

 

In practice, sources of error can be found throughout the value chain of data management. These can be human input errors during data acquisition, defective sensor data or incomplete data imports in automated processes. But also, different formats of data can lead to errors, in the simplest case when one has to input the data in US, in case of uncertainty about whether the metric or imperial (Anglo-American measurement system) is used. In addition, organizational deficiencies lead to data errors, for example, if it is not clearly defined who is responsible for which data sets.

 

In order to achieve more quality data, five points can be identified that help to increase the value of your own data.

 

Clarify goals:

 

Everyone involved in the project should agree on the business goals to be achieved with an initiative for better data quality. From sales to marketing to management, each organizational unit has different expectations. While decision-makers need more in-depth analysis with relevant and up-to-date information, it may be critical for a sales representative that address data is accurate and complete.

 

Find and catalog data:

 

In many organizations, data is available in a variety of formats, from paper files and spreadsheets to address databases to enterprise-class business applications. An important task is to localize these databases and to catalog the information available there. Only when the company knows what data can be found in which database and in what format, a process for improving the data quality can be planned.

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Harmonization of data:

 

Based on the initial inventory, a comparison is now made with the target to be achieved. This can result in a variety of tasks, such as a standardization of spellings, data formats and data structures. It uses tools for data preparation and deduplication to provide a harmonized set of data, while data profiling solutions help analyze and evaluate data quality.

 

Analysis, evaluation and processing:

 

If you consolidate your data and process it in a cloud, data lake or data warehouse, you can flexibly perform a wide variety of data preparation tasks there by using data integration and data management software solutions. Anyone who has to process streaming data, originated from sensors or Internet of Things, has the option of using cloud resources to check the incoming data in a very flexible way and to sort out fake data packets.

 

Establish continuous processes:

 

Ensuring data quality is a continuous process. After all, new data is always collected and integrated into our own systems. Even if external data sources already provide high-quality data for further processing, it is still necessary to constantly check and validate your own data stocks via a data monitoring system. There are very different solutions, such as, self-service data cleansing solutions, rule-based data transformation applications, self-learning software solutions that independently monitor data formats and detect and correct statistical anomalies. Already today, algorithms for deep learning or artificial intelligence are able to handle many tasks around data management in big data scenarios. However, it is important that responsibilities for data management are named and that quality assurance processes are confidently secured in the company’s processes.

 

Conclusion:

 

Managing quality data is a team work that spans in all functional areas of a company. Therefore, it makes sense to provide the employees in the departments with tools to secure the data quality in self-service. In particular, cloud-based tools that can be rolled out quickly and easily in the departments are ideal for this. Thus, equipped companies can succeed gradually in improving their data quality and increasing the value of their data. This leads to satisfied employees and happy customers.

How To Better Secure Multi-cloud Environments?

The rise of cloud-based services and a variety of choice regarding the cloud has filled the market with more competition than ever before.Increasingly, organizations are now choosing to mix and match cloud solutions. Butare they ready for the security challenges of multi cloud architectures? Applications that are spread across different cloud providers are extremely difficult to see; visibility is often limited. How businesses can better manage their multi-cloud infrastructure explains Jeff Harris, VP, Product Portfolio Marketing from Keysight Technologies.

cloud Workloads

The year 2017 was marked by a strong increase in enterprise cloud computing. According to Gartner, 90% of global companies currently use at least one cloud service. But today, no one is limited with just one cloud service, and even companies working with only a single cloud service provider doesn’t exists anymore. Multi-cloud, the use of multiple public clouds, is quickly becoming the next step in building truly dynamic infrastructures. By dynamically executing workloads across multiple cloud providers, organizations can ensure that workloads are truly optimized. The above-mentioned Gartner study reports that 70% of businesses plan multi-cloud implementations by 2019, up from 10% of today.

 

Up mentioned study also shows that 93% are concerned about security in cloud. But are companies ready for the security challenges of multi-cloud architectures? Each cloud provider has its own technological details as well as unique cloud services and management interfaces. It can be difficult to build an integrated view of the action. As a result, organizations may not really know if their security policies are constantly applied to workloads that are spread across multiple cloud providers – and may dynamically switch between them.

 

Businesses could easily trust cloud providers to protect their data, but that would not be a good idea. Security breaches and data theft are quickly becoming public. Ignorance is simply not an acceptable defence. In addition, a lack of insight into the individual processes or lack of evidence of compliance is enough to make most audits fail.

 

Ultimately, the operators of those applications are always responsible for data security in multi-cloud environments, but most do not have enough visibility and therefore no real control – they cannot really ensure that their data is 100% secure. However, there are approaches to make sure that their data is safe. Here are four steps companies can take to better manage their multi-cloud infrastructure:

 

  • Monitoring of data at the package level

    To monitor their traffic, organizations need to have data access at the packet level. The data provided by the cloud providers is not yet what IT managers in their own data center are used to. For example, metrics can be obtained through Cloud instances, but typically not the actual packages themselves. In addition, the metrics may not be as complete or available for a limited time. There may not be an easy way to build the custom dashboards needed to detect network and application performance issues. These limitations make it harder and more time-consuming to identify and resolve security and performance issues.

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  • Treat all data equally

    Once available, organizations need to integrate cloud packet data into existing IT service management (ITSM) solutions, where they can be centrally monitored along with other system management data. This allows organizations to perfectly monitor the performance, availability, and security of workloads, regardless of the underlying infrastructure, while providing a foundation for policy enforcement. This central monitoring and policy enforcement ensures that the company has control over the security of its own data and that policies are consistently applied to all workloads, whether they are in the data center, on the infrastructure of a single cloud provider, or across multiple cloud sites architectures.

 

  • Understand context and apply intelligent policies

    Like all monitoring data, cloud package data must be placed in the right context for analysis. To determine if a package is good or bad, it must be fed into the appropriate monitoring, compliance, analysis and security appliances where it can be converted into actionable information. CRM data is treated differently in the data center than HR documentation. So why should a company handle it differently when they come from the cloud? Insight at the network packet level, it’s easier to identify and route data according to existing policies. The result can be seen in more robust security, improved network performance, and better resource allocation.

 

  • Apply your own test procedures

    You should trust your own tests more than anyone else. Cloud providers do their best, but they need to serve the masses of customers, not individual needs. It’s important that organizations constantly test the performance, availability and, most importantly, the security of their workloads in multi-cloud environments. One-time testing provides a degree of security, but continuous testing adds confidence in cloud security – especially as cloud applications are generally subject to constant change.

 

Businesses will increasingly use multi-cloud architectures, as users always demand optimized experiences. The ability to move workloads across clouds allows for this optimization; however, security remains an important concern in multi-cloud agreement. Businesses can do this by implementing the same packet-level network transparency they use on their private networks. Seamless access to cloud package data provides the ability to route information to any security, monitoring, and testing tools, where it can be analyzed and evaluate. Even in a multi-cloud environment, you can implement strong security solutions. It only requires planning and consistent execution.

 

Data Privacy Policy: Consumers Trust In Organizations Diminished

The results of Veritas Technologies’ global research have revealed that consumers around the globe are less and less confident about data privacy policies held by companies and have issues with trusting the organizations to protect their personal information. With each new data leak and successful hacker attack their uncertainty grows, at a point where 38% of worldwide consumers are persuaded that most businesses don’t know how to protect their customer’s data.

 

Results also highlight that consumers want to penalize companies that are bad at protecting their data. On the other hand, companies that place a high value on data protection should be rewarded.

Consumers Trust iIn Organizations Diminished

 

In today’s competitive world, most worldwide companies need data to effectively target consumers with the right goods and services to deliver a better experience. But with the introduction of New strict compliance rules such as the EU GDPR, consumers will have more power over their data in the future. Many consumers will impose companies to better protect their personal data as they need reassurance when it comes to what personal data are companies holding, how it is used and how it is shared.

 

The new norm

 

data privacy gdpr

 

The study, commissioned by Veritas and conducted by 3GEM, surveyed 12,500 people in 14 countries including UAE. Results show that 92% of respondents are concerned about exposing personal data, 40% of respondents have no visibility into how their data is used and 83% are not satisfied with companies not knowing how to protect their data.

 

With the GDPR regulations, 65% of respondents says that they’ll request an access on their personal data that companies are holding and 71% will even ask them to delete their data.

 

Almost three quarters, 71%, of respondents say they will stop buying from a company that does not adequately protect their data. And nearly every second, 43%, would abandon its loyalty to a particular brand and switch towards a direct competitor. It can even be a worse scenario for companies because 79% say they would recommend their surroundings to boycott the organization in case of data breach and 87% claim they would report the business to regulators. 69% of respondents say they would post negative comments online about the business.

 

However, the survey also shows that good data protection pays off. So, consumers want to reward companies that protect well their data. Four in five respondents, 80%, say they would spend more money on companies they trust to guard their data. More than a quarter, 30%, of consumers are willing to spend up to 25% more on companies that take privacy seriously.

 

“Trust in consumers has been eroded by many data breaches and global scandals as companies have revealed a lack of understanding of data privacy protection,” said Tamzin Evershed, Senior Director and Global Data Protection Officer at Veritas. Consumers demand more transparency from companies and demand accountability from them. Under this new norm, consumers will reward those organizations that carefully manage data while punishing those who do not. Businesses need to prove themselves as reliable data managers in order to retain the trust of their customers.

 

Growing concerns about the collection of personal data

 

As consumer interest is rapidly growing in how personal data is used and shared by companies, the study shows that consumers are no longer prepared to share the following types of personal information:

 

  • Details about personal finance including income, mortgage (49%)
  • Details on health and medical records (24 percent)
  • Age and gender (29%)
  • Location (36%)
  • Online habits (35%)
  • Religious preferences (38 percent)

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In addition, consumer doubts about how their data is shared with companies and third parties. Nine out of ten respondents (89%) said they were worried about protecting their personal information. Almost half of the respondents (44%) say they have no idea how companies use or share their data. After all, 30 % fear that their personal information will be stolen.

 

“In light of recent events and changes in the law, consumers need much more reassurance when it comes to what personal data companies hold on them, and how it is shared and used,” said Tamzin Evershed, Senior Director and Global Data Protection Officer at Veritas.

 

“This could have significant implications for businesses that rely on collecting consumer data to provide intelligent and targeted services, such as location-based apps. The most successful companies will be those that are able to demonstrate that they are managing and protecting personal data in a compliant way across the board.”

 

Big Day for your Data – What did GDPR changed from 25 Mai 2018?

As from 25/05/2018, the new European data protection rules (GDPR) from companies and governments require that they use your data more carefully. Otherwise, companies and governments can be expose to the risk of huge penalties.
After a start-up period, companies operating in the European Union must henceforth be in line with new data protection rules. Thanks to the rise of online services, such as social media and e-commerce, more and more companies have access to your data. GDPR have to make sure that they take your privacy seriously this time.

 

GDPR compliance report from Crowd Research Partners and Cybersecurity Insiders in partnership with the 400,000+ member of Information Security Community on LinkedIn reveled thatGDPR is a priority for the vast majority of respondents (80%); for a third of respondents (34%) it is one of the top three priorities. 20% say GDPR isn’t a priority – but that won’t relieve them from having to comply with the law.

 

GDPR COMPLIANCE PRIORITY

 

What is it about?

 

As already explained in detail in our previous blog posts, the idea behind the General Data Protection Regulation (GDPR) is that you retain control over who uses your data and for what purposes. Companies that want to send you a newsletter or promotional e-mail must have your explicit permission. The request for permission must also be specific, clear and not ambiguous.
But the requirement to ask for your permission does not always apply. Sometimes a company needs your data to be able to deliver a product or service. If you want a parcel to be delivered through a webshop, it needs your address. You are then in a contractual relationship. Governments can also process data without permission as they have legal obligations to fulfill.

 

What can you expect?

 

You’ve probably received a rain of mails during the last few days and weeks. These are meant to ask for your permission to keep contacting you. But companies, if properly prepared, also present new privacy tools in the same mail. This is mostly a dashboard where you as a customer can change your privacy preferences at any time.
After all, it is not because you once gave your permission to process your data, that this always has to be the case. The new rules stipulate that you can view, modify or remove your data at any time. At least: you can submit a request for it. Companies still have a lot of work to do that.

The new rules must also allow you as a customer to ‘take’ data with you. If you changed telecom operator in the past, you had little say on what happened to your old data provider with your data. Now you have the right to have the data removed and your data, ‘in a readable format’, with you. That can feed competition.

 

What if you did not respond to any e-mails?

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We all saw emails coming in with the question from companies if they could still contact you. Companies that do not have your explicit permission and still contact you from today onwards, in theory, is illegal.

 

What are the concerns for companies?

 

The first question that every company must ask itself is whether it processes personal data. This includes the disclaimer that there are few companies that do not collect or process data. Personal data are not only limited to the data of customers, but also those of employees.
For that reason, personal data is often distributed throughout the entire company, from customer service to HR. A good first step is setting up a data register, which maps out which department processes which type of data. The company can then make a privacy statement, which lists which data are kept and for which reason. A number of specific companies that collect sensitive data on a large scale must also appoint a data protection officer from now on.

 

Are companies ready?

 

It won’t sound so shocking if I say that most of companies aren’t ready. GDPR compliance report from Crowd Research Partners and Cybersecurity Insiders in partnership with the 400,000+ member of Information Security Community on LinkedIn reveled that 60% of organizations are at risk of missing the GDPR deadline. Only 7% of surveyed organizations say they are in full compliance with GDPR requirements today, and 33% state they are well on their way to compliance deadline.

GDPR PREPAREDNESS

 

What are the challenges in GDPR adoption?

 

Up-mentioned study shows that the biggest challenge in GDPR adoption is related with lack of expert staff (43%), followed by lack of budget (40%), and a limited understanding of GDPR regulations (31%). A majority of 56% expect their organization’s data governance budget to increase to deal with GDPR challenges.

COMPLIANCE CHALLENGES

Who checks and what are the fines?

 

The majority of the GDPR regulation is a repetition of previously existing principles. The big difference is that European companies that are too lax with your data can now be hit in their wallets. With a maximum of 20 million euros or 4% of the annual turnover.

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