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Pros of a Multi-Cloud Strategy

Multi-cloud Popularity

Did you know that 77% of enterprises have at least one application or a portion of their enterprise computing infrastructure in the cloud? Did you also know that enterprises are increasingly putting money in the cloud and 15% of them intend to adopt cloud apps and platforms in the next 12 months? This is according to the Cloud Computing study conducted by IDG in 2018.

 

With the rise of tech, even an ordinary individual like us uses the cloud, especially when we’ve to manage photos, files, and documents on various websites and apps such as dropbox, iCloud etc. Business-wise, though, 77% of enterprises are using cloud apps, platforms, and services, as mentioned above. Enterprises have different use cases of cloud computing but there are those who go beyond the ordinary use cases. These innovative companies conduct cloud management, by using public, private, and hybrid clouds, to drive growth and to adapt to an ever-changing technological landscape. In addition to that,Multi-cloud concepts are on the rise as companies seek more choice about the best place for their data and workloads.

 

Before understanding a multi-cloud strategy, it’s recommended to differentiate different type of clouds, such as, public, private and hybrid.

 

A public cloud is provided by companies like Amazon, Microsoft, Google, and IBM and t you can pay on a subscription basis or on a pay-as-you-go model. A private cloud, on the other hand, is for the use of a single company only. It is designed for the unique infrastructure of an organisation and for its use case and can be deployed on-premises or in data centres that offer colocation services. Lastly, the hybrid cloud is a combination of at least one public and one private cloud services. They are unique entities but are connected with different technologies.

 

Multi-cloud concepts are on the rise as a growing number of companies seek more choice about the best place for their data and workloads in order to meet various business and technology requirements because no single cloud model can fit the diverse requirements and workloads across different business units. The multi-cloud is more than just the parallel use of multiple clouds. It’s a comprehensive strategy to make the most of each of the available cloud technologies. Since many companies already use different cloud technologies, the question arises of how to bring these technologies under one umbrella. IT teams are looking for ideas, strategies and solutions to take the next step towards a unified multi-cloud.

 

So, In the process of cloud adoption, here below are few tips of what IT teams should consider to take full advantage of the flexibility of the cloud to adopt a multi-cloud strategy with the help of three key technologies that are important in building a multi-cloud environment.

 

As legacy tools aren’t compatible for work in new multi-cloud environments, it’s is necessary to adopt new solutions to give organisations the freedom to move to, from, and between any combination of clouds, and by far the main benefit of creating a multi-cloud infrastructure is that it provides enterprises with the flexibility needed to innovate at speed.The reason for this is that it doesn’t tie them to the specific set of services provided by various individual cloud providers. As a result, the way an enterprise chooses to innovate is its own.

 

However, using software and tools that are not specifically designed for multi-cloud scenarios can be an incredibly frustrating process that completely rejects the benefits of the multi-cloud. To effectively implement a true multi-cloud strategy, organisations should not seek to integrate legacy tools into their new environments. Instead, they should introduce new solutions that are focused on the future. There, the majority of businesses use more than one cloud platform to keep their workloads and data in the ideal place while fully protecting it.

 

The multi-cloud offers great benefits for businesses that can get the most value from any platform but at the same time, it brings new challenges of removing barriers to data and cloud storage management. To maximize the benefits and meet the challenges, organizations need a scale-out storage solution that bridges the gap between local and cloud environments and allows users to combine data in private and public clouds around the world as a single unified management. This allows users to store, protect and search data from a management interface, regardless of where the data is physically located.

 

Opting for multi-cloud solutions means opting for a cost saving strategy. As each cloud provider offers different storage options at different price packages, companies can easily meet workload performance requirements at a very interesting price. In addition to that, having a multi-cloud is also beneficial to avoid any vendor lock-in.

 

No doubt that a multi-cloud strategy allows organisations to create the best cloud solution for their business by taking advantage of the best of what each cloud offers, minimises vendor lock-in, and provides more opportunities for optimization.

 

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RPA & AI in Health Care

Smart systems affect our professional and private lives. Artificial intelligence (AI) is getting sophisticated and forming the basis for all the technologies we use on a daily basis. Obsolete technologies are making ways for new systems, entrepreneurs must reorient and restructure their business processes towards digitisation. As AI is getting increasingly sophisticated at doing what humans do, more efficiently, more quickly and at a lower cost, it’s use in healthcare can play a major role. Many industries already rely on automation of business processes using robotic process automation (RPA) or even artificial intelligence. Is this a good solution for the healthcare industry too?

 

With the advancements in technology applications and apps that encourage healthier behaviour, the population is increasingly having longer life expectancies. Hospitals struggle with mountains of data and inefficient and complex ways of processing all these data. Moreover, caregiver spent a significant amount of their time doing these repetitive tasks.Thus, the need for medical care is growing and the shortage of skilled workforce in the care sector is growing as well.

 

The complexity and rise of data in healthcare means by making AI and robotics a part of our healthcare Eco-system, and with the integration of automation of processes, we can counteract these problems. With the use of software robots, we can shifts repetitive, time-consuming routine activities, such as administrative or billing operations, away from employees to virtual “colleagues”. Faster access to data also makes medical care easier for patients: with the data generated via patient wearables and other medical devices combined with AI, it’s helpful to oversee early stage heart disease, enabling doctors and other caregivers to better monitor and detect potentially life-threatening episodes at earlier, more treatable stages. Doctors and caregivers can have more personal contact with patients and often fewer mistakes.

 

AI can be used to analyse and identify patterns in large and complex datasets faster and more precisely than it has previously been possible. It has the potential to aid the diagnosis of disease. Using AI to analyse clinical data, research publications, and professional guidelines could also help to inform decisions about patient’s treatment. But as AI depends on digital data, so any inconsistencies in the availability and quality of data restrict the potential of AI. 

 

Robotic Process Automation is digital techniques form an interface between the management concept and the automation of business processes using software solutions. Virtual employees take over the handling of individual user interfaces or even entire business processes. With the help of automation, workers get more time for tasks that require individual interaction and emotional judgment. Software robots mimic and perfectly scalable business processes in all areas around the clock with almost zero error rates.

 

Opting for RPA can represent a lot of advantages for medical institutions, such as:

 

  • Automation of routine tasks = relieves employees of frequently repetitive tasks so they can apply their skills to cases that require a human touch
  • Process, input and extraction of user interface-driven data from clinical applications, lab information systems, third party portals, insurance portals, radiology information systems= increase productivity and improves quality of work
  • Software robots work faster without any human error = Patient’s data up to date
  • An RPA robot can enter pertinent and specific health information into a patient’s Electronic Medical Record (EMR).
  • With the use of RPA, doctors have patient’s digital traces all the time = more insights into work process flows
  • RPA productivity also translates into return on investment as Software robots work much faster than their human counterpart
  • Helps caretakers not only reduce costs and gain efficiency but also increase the quality of patient care and amount of time spent with them
  • RPA can optimise patient registration, appointment scheduling, billings and payment posting = decrease in operational costs and improvements in patient experience 

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RPA is offering great benefit to health care professionals and administrators in helping them perform their tasks at a higher capacity with less effort. The combination of RPA and artificial intelligence forms the next level of automation because systems make their own decisions, learn and optimise processes independently. AI can assign tasks, which are then executed by RPA. The software robots provide the hands for the cognitive systems. In the future, for example, automation solutions could be even more involved in the monitoring of people in need of care. However, it often turns out to be sufficient and above all more meaningful to use RPA alone as it enables them to provide immediate productivity gains, achieve near zero error rates, reduce operational costs and greatly increase the quality of patient care.

 

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All-inclusive Security Approach for Next-Gen Endpoint Terminals

All-inclusive Security Approach for Next-Gen Endpoint Terminals

In the last 20 years of the information technology and the advancements of the cyberspace landscape has advanced non-stop, that’s why the future of cybersecurity is strongly connected to IT advancements. Along with the development in IT, cyber-hackers have also updated their strategies to evade the security measures in place, and the terminals remain their favorite targets.

 

Many studies have demonstrated that, in 2019, businesses of all sizes have faced more sophisticated and more dangerous cyber-attacks. Only in the first half of 2019, over 4.5 billion records from organizations around the word have been compromised via data breaches and cybersecurity attacks.

 

Now, with the cloud, IOT and mobile devices, endpoints have become the company’s new security perimeter. It is therefore increasingly critical to lock and secure them. There’s no doubt that companies continuously deploy numerous software on devices to secure them, such as, antivirus, firewall, intrusion detection, vulnerability management, Web filtering, antispam and many others. Yet, despite those solutions in place, many companies still suffer from security breaches.

 

In addition to that, as the trend of remote working is also escalating in 2019, companies are facing security challenges in terms of security and data protection, for those employees that are using their own devices, outside of business networks, or company premises. Therefore, securing Endpoint devices can be very challenging, especially when employees are using their own devices for work or using their work devices for personal usage out of company premises. And if they get their device stolen or hacked, it could lead to huge disaster, such as company accounts can be compromised. Therefore, YES, organizations and business around the world need to invest in Endpoint Protection solutions. With the help of these solutions, Endpoint devices can be secured with cloud based anti-virus installed on each Endpoint Device. And they need next generation protection in addition to their antivirus, prevention and detection of advanced threats.

 

Here below are listed few important criteria’s that companies need to take in consideration for a comprehensive endpoint security strategy: 

 

  • Preventing any attacks requires more than just a firewall or a single antivirus program. By implementing a combination of security strategies, including device firewalls, specific email Antivirus tools, internet security, mobile device management and security solutions, encryption and intrusion Detection tools, companies can avoid malware and stop it in real time. In addition, vulnerabilities can be identified and remedied to prevent malware entry. Importantly, prevention must cover the entire corporate network, including all endpoints.

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  • IT security teams must analyze and record, nonstop, each endpoint activity so they can detect all activity connected to any type of attack, including known vulnerability exploitation, zero-day attacks or non-malware- related intrusion.

 

  • 100% malware protection is not possible today, therefore, companies must opt for a system with which they can secure their endpoints round the clock and have an eye on any malicious behavior. They must learn from any past experience by understanding the actions an attacker may take in order to penetrate company’s network so they can enhance their security for future and also take things in control after a breach.

 

  • Administrators must be able to view activity that happens on the corporate network at any time in present or past. All endpoint security solutions must be able to offer real-time interactive reports on user activity. An overall view of the reports for events that occurred in the past must be available at anytime.

 

  • IT security teams must secure and enforce security policies on the all company devices, even those that employees can take out for remote working. They must install a suite of security control that protects sensitive data on those devices and endpoints by encrypting sensitive corporate data.

 

Sources:

Forrester: Rethink Enterprise Endpoint Security In The Cloud Computing Era

 

IBM: Protect critical assets: Safeguarding data, apps and endpoints

Top Strategies to Improve and Increase Data Quality

Top Strategies to Improve and Increase Data Quality

 

Organizations face enormous amount of pressure when it comes to face the issue related to data quality. Businesses can only make the right data-driven decisions if the data they use is correct. Without sufficient data quality, data is practically useless and sometimes even dangerous.

 

Regardless of whether your data is structured or unstructured or your data is on-premises or in the cloud, it needs to be on top to deliver business value by ensuring that all key initiatives and processes are fueled with relevant, timely and trustworthy data. Because bad data quality not only costs time and money, in the worst case, it even leads to significant revenue losses.

 

But despite its importance of having data quality, the reality in many of today’s organizations, data quality has been voted among the top three problems for BI software users every year since the first issue of The BI Survey back in 2002.

 

What is data quality?

Defining data quality depends on the needs of each organizations. It can differ from one business to another. As a poor quality of data, especially of customer data, quickly leads to serious problems, therefore for some organizations, it can be ensuring that customer contact data is up to date so that deliveries are received in a timely manner. For other organizations, it could be filling prospects profiles that can be helpful with marketing segmentation effort. Serval factors are being used to determine the quality of data, such as accuracy, completeness, relevancy, validity, timeliness and consistency.

 

Here below are few examples to clean up and improve the consistency and reliability of your data:

 

  • Understand the purpose of your data

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IT department should work with other departments of company to align and acknowledge the problems and negative impact that company can face because of missing or erroneous data. Even though a lot of data today are generated, companies must make a strategy about what data is been collected and for which purpose the gathered data can be used because the collected data should ultimately exist for a business or mission purpose.  For this purpose, they must work to identify incomplete, faulty or multiple existing customer data, because very often, in different departments, different inventory data exists for the same customers. So, paying attention to an error free data can lead to increase data quality.

 

  • Get a Data Control Supervisor from a Qualified Department

Data Control supervisors play a crucial role in the success of a data quality mission. They come from a specialist department and know how to oversee the development and use of data systems. They can discover efficient ways to organize, store and analyze data with attention to security and confidentiality. He is also responsible for creating and enforcing policies for effective data management, formulating management techniques for quality data collection to ensure adequacy, accuracy and legitimacy of data, devising and implementing efficient and secure procedures for data management and analysis with attention to all technical aspects. His goal is to ensure that information flows timely and securely to and from the organization as well as within.

 

  • Implement a priority list of undesirable data

Today many companies are using different equipment (IOT) that records vast volumes of sensor data. Unfortunately, not all the gathered data in company is valuable. Therefore, Data Control supervisor must perform quality checks in order to reject undesirable data. To do this, he must be able to respond to following questions: How and by whom was the data generated? Which users are accessing it? For what purposes are they used by which applications? Which costs cause faulty data?

 

  • Prevent duplicate data

Duplicate data refers to when the same information is somehow input as two separate entries by different people or teams

In the presence of duplicate data, it is very hard to pull out exact results or CRM and Marketing campaigns and can create serious issues when you’re creating automations, looking up buying patterns, or putting together a target audience. So, Data Control supervisors must make sure that company is using a data management software that regularly checks the data for duplicates and cleans it to ensure that their data is clean, has quality, and is reliable to work with.

 

  • Perform regular checks on your data to uncover anomalies

If you want to understand and ensure your data quality, you have to perform regular checks to see if there’s no “bad-data”. Reviewing your data will help you to understand if the gathered data aim for organisations objectivity. As getting 100% data accuracy is not the final objective, Data Control supervisors must be able to pull-up the insights from the data to it’s main goal. Improving data quality is an ongoing process and it takes time to get it right.

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