Paulding-Putnam Electric Cooperative Transitions IT Infrastructure to the Cloud to Provide a Superior Customer Experience - PDF
Paulding-Putnam Electric Cooperative Transitions IT Infrastructure to the Cloud to Provide a Superior Customer Experience
Organizations Shift to Cloud-Based Analytics and IT Platforms
The growth rates of cloud-based IT solutions in the areas of analytics and artificial intelligence have been substantial in recent years. The increasing volume of data and the need for faster, more accurate insights have driven organizations to adopt cloud-based analytics solutions at a rapid pace. This has resulted in the growth of cloud-based data warehousing, business intelligence, and big data analytics solutions.
Similarly, the growth of artificial intelligence has been driven by the cloud, as it allows organizations to access powerful AI algorithms and training data without having to invest in expensive hardware. The cloud has also made it possible for organizations to scale AI solutions quickly and easily, leading to an increase in the adoption of cloud-based machine learning and deep learning solutions. These trends are expected to continue as organizations look to leverage the power of AI and analytics to gain a competitive edge in the market.
This growth in cloud-based analytics and AI has been driven by the larger business adoption of cloud IT because of its numerous benefits such as increased flexibility, scalability, and cost savings. Cloud technology allows companies to access their data and applications from anywhere, reducing the need for physical infrastructure and freeing up resources for other areas of the business. This shift towards cloud computing has also improved disaster recovery and business continuity, as data can be stored and accessed remotely. Additionally, with the rise of cloud-based solutions, businesses have been able to access advanced technologies and services without having to invest in expensive hardware and software. This has resulted in increased competitiveness, innovation and better overall business performance.
APIs add efficiency and flexibility to cloud environments
The power behind the most widely adopted cloud platforms are APIs (Application Programming Interfaces), which play a crucial role as they allow different software systems to communicate with each other and access data from the cloud. This has enabled organizations to build custom solutions and integrate disparate systems seamlessly, making the use of cloud technology much more efficient and flexible.
APIs also allow for automation and streamlining of processes, reducing manual errors and freeing up time for more valuable tasks. APIs make it possible to add new functionality and services to existing systems, allowing for continuous improvement and innovation. In essence, APIs provide a bridge between the cloud and an organization’s systems, enabling organizations to harness the full potential of cloud computing and drive digital transformation.
Analytics moves to the cloud
In terms of business outcomes, cloud-based analytics allow businesses to access and process large amounts of data in real-time, regardless of the size or location of their operations. This enables organizations to make informed decisions quickly and respond to changing market conditions with agility. Secondly, these solutions are much more cost-effective, as businesses only pay for what they use and do not have to invest in expensive hardware or IT infrastructure. The cloud provides businesses with access to a wide range of advanced analytics tools and technologies, enabling them to gain insights from their data in new and innovative ways. These solutions are highly secure and reliable when they are managed by experienced cloud service providers who ensure that data is protected and the solution is always available. Overall, they are considered to be a better choice for businesses because of their scalability, flexibility, cost-effectiveness, and secure approach to data analysis.
Likewise, cloud-based AI or AI as a Service (AIaaS) provides organizations with access to deep insights without having to invest in expensive experts or the necessary hardware and software to implement such solutions. This makes it easier for organizations to deploy and scale AI solutions as they only pay for what they use and do not have to invest in maintaining their own infrastructure. Furthermore, these solutions are more flexible and can be customized to meet specific business requirements, enabling organizations to generate valuable insights that help them to differentiate from their competitors. Finally, cloud-based AI makes it possible for organizations to collaborate and share AI models, allowing them to leverage the collective expertise of their partners, customers, and employees to create better solutions. In short, it is a high-value choice for businesses as it provides a more accessible, scalable, affordable, and collaborative approach to artificial intelligence.
Moving to the cloud accelerates digital transformation
Leading research and advisory firm Gartner reported that “Cloud migration is not stopping, IaaS will naturally continue to grow as businesses accelerate IT modernization initiatives to minimize risk and optimize costs. Moving operations to the cloud also reduces capital expenditures by extending cash outlays over a subscription term, a key benefit in an environment where cash may be critical to maintain operations.”
Aunalytics provides a highly redundant and scalable cloud infrastructure that enables midsized businesses to reap the benefits of the cloud at a reasonable cost. The Aunalytics Cloud provides a wide range of solutions—including cloud storage, backup and disaster recovery, application hosting, advanced analytics, and AI. Moving from on-premises computing to a cloud environment is a key step in an organization’s digital transformation.
Overcome Hiring and Talent Challenges to Get Ahead of the Competition in 2023
Overcome Hiring and Talent Challenges to Get Ahead of the Competition in 2023
Hiring and retaining staff is going to be the most difficult task facing CFOs for much of 2023. This is particularly true for IT departments. In today’s economy, highly skilled IT and data experts are a scarce and expensive resource. The mid-market organization requires another option that provides access to the right tools, resources, and support.
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Ransomware Attacks in Manufacturing Pose An Increasing Threat
Cyberattacks are a constant threat to organizations of all sizes. Manufacturing and production industries may have experienced fewer cyberattacks than other industries, but companies are still at risk from bad actors. To gain a better understanding of the current attack environment and track changes over time in ransomware trends, Aunalytics security partner Sophos commissioned an independent, vendor-agnostic survey of 5,600 IT professionals in mid-sized organizations across 31 countries. Out of all the respondents, 419 were from the manufacturing and production industry. This survey was conducted in January and early February of 2022. While it’s true cyber insurance has been playing a greater role in helping organizations improve their ability to recover from attacks, survey responses clearly indicate the rising threat ransomware poses to the manufacturing industry.
Cyberattacks Are Up From Previous Year
Ransomware attacks have increased significantly over the past year—55% of manufacturing and production organizations surveyed were hit by an attack in 2021, up 36% from 2020. Bad actors are now considerably more capable of attacking businesses and executing harmful tactics at scale. The Ransomware-as-a-Service model is one cause of this year’s increased attacks, as the required skill level for bad actors to hamper the day-to-day operations of an organization has gone down significantly.
Apart from the rising prevalence of these attacks, the sheer complexity of each attack is also on an upwards trajectory. While the manufacturing and production industry reported the lowest rate of ransomware attacks, but, with over half of all respondents in all surveyed industries reporting that their company was been injured by bad actors, the reality is that every organization is at high risk of attack. In 2021, 57% of attacks in the manufacturing and production industry resulted in important data being encrypted. Additionally, 59% percent of organizations who experienced cyberattacks saw the complexity of the attacks increase, while 61% saw an increase in the overall volume of cyberattacks.
Data Recovery Rates Are Improving
While the increase in cyberattacks paints a bleak picture, there is a silver lining to this dark cloud. 96% of manufacturing and production organizations were able to get some of their encrypted data back. The top method used to restore data was backups, which were used by 58% of organizations whose data was encrypted in an attack. Unfortunately, despite the utilization of backups, a third of the effected organizations still had to pay a ransom to ensure that more their data was restored.
Unfortunately, while paying a ransom typically allows organizations to get some data back, it is proving to be less effective than in years past. On average, in 2021, organizations that paid a ransom only got back 59% of their data, and only 7% of those that paid the ransom got ALL of their data back. This highlights the importance of employing multiple methods to restore data—utilizing backups in particular can improve the speed of recovery and increase the amount of data that can be recovered in the event of an attack.
Ransom Payments Have Increased
The average ransom pay-out has seen an exponential increase from what was reported in 2020 data, rising from an average of $147K (USD) to a jaw-dropping $2,036,189 (USD) in 2021.
Ransomware Has a Massive Impact on a Company’s Financial Status and Operational Capacity
Even when some of the encrypted data is restored after a cyber-attack, there are additional costs in the form of lost productivity and a decline in operational capacity, which can have a considerable impact on your company. Of those hit by ransomware last year, 77% said their most significant attack impacted their ability to operate, while 71% said it caused them to lose business and/or revenue. The average cost to remediate an attack in 2021 was $1.23M (USD), down from $1.52M (USD) in 2020. This was due in part to cyber insurance providers being able to better guide victims through an effective response more rapidly.
Although there have been improvements in total recovery time over the years, it still took, on average, one week for manufacturing and production organizations to fully recover from the most significant attacks.
Despite the huge economic costs of ransomware attacks, many organizations are continuing to put their faith in defenses that don’t actually prevent ransomware—only more quickly mitigate its effects. Most of the organizations in the survey who weren’t hit by ransomware in the past year and didn’t expect to be hit in the future cited backups and cyber insurance as reasons why they don’t anticipate an attack. It’s important to note that neither of these elements can actually prevent cyber-attacks.
Simply having security mitigation resources in place does not mean that they will be effective against malicious attacks. Despite having ample resources—in both personnel and technology—organizations will not achieve a high return on investment without a combination of the right technology and expertise to use the technology effectively.
Cyber Insurance Drives Changes to Cyber Defenses
Thankfully, organizations do not have to shoulder the burden of ransomware costs all on their own. The survey found that three out of four manufacturing and production organizations had insurance against ransomware attacks. Organizations that had been previously hit by ransomware attacks in the past were much more likely to have cyber insurance coverage against ransomware. However, many respondents indicated that securing coverage has changed or gotten more difficult to obtain in the past year:
- 56% said the level of cybersecurity they need to qualify is now higher
- 53% said policies are now more complex
- 42% said it is more expensive
- 35% said fewer companies offer cyber insurance
- 30% said the process takes longer
As a result, 97% of organizations that have cyber insurance have made changes to their cyber defenses to improve their cyber insurance position. 70% have implemented new technologies and services, while 63% have increased staff training and educational activities, and 59% have changed processes and behaviors.
But It Doesn’t End There
The State of Ransomware 2022 survey by Sophos has revealed that ransomware continues to be an imminent threat for the manufacturing and production industry. For many, choosing an experienced partner with expertise in cybersecurity not only improves their chances of getting approved for the right amount of cyber insurance coverage, but can also ensure that companies see an higher return on investment and improved ability to both prevent and mitigate attacks in the future.
Cloud or On-Prem Servers—Which Is Better for Your Company?
Every organization needs to manage its data to get its desired business outcomes. For a company to access its data and use it in day-to-day operations, dashboards, reporting, and data analytics, it either needs a cloud or on-premises solution to facilitate compute, storage, and data management strategies.
What’s The Difference Between The Cloud And On-Premises Data Storage?
An on-premises data server is hardware that you maintain on your company’s premises for storing, processing, and accessing information through your organization’s networks. An in-house IT department is needed to maintain, turn over/replace, and upgrade the hardware, keep it stable and operational, and secure it.
A cloud storage solution run by an expert and backed by a cutting-edge data center provides the same functions as an on-premises server and more. It does not exist on your company’s premises and the data on it is accessed through the internet. All updates and maintenance tasks are performed by the cloud provider, who owns and operates its own hyper-secure data centers to safeguard your data in case of failure, cyberattack, or outage. Like on-premises servers, access to cloud data can be set by administrators to be permission-based to allow access only by authorized personnel.
On-Premises vs. Cloud—Which Option Best Suits Modern Business Needs?
There are more factors when choosing between using a cloud computing solution or keeping servers on-premises, including customizability and scalability, security concerns, and the budget for your organization’s data management strategy. While on-premises data servers regularly require hardware upgrades in your physical locations to expand alongside your business’s growing needs, a cloud storage and computing solution with access to highly advanced data centers is scalable based upon your workload. Unlike an on-premises server that can take a lot of time and money to set up and ready for operation, cloud service providers ensure you can access your cloud for computing and storage needs almost instantly.
In some mid-sized companies, server rooms tend to be used for multiple purposes, which means that they are sometimes unlocked, unsecured, and allow for unauthorized access that compromises data security. Many mid-sized companies do not have 24/7/365 monitoring of their server rooms, specialized climate controls needed for a data center, and do not consistently deploy or regularly schedule hardware upgrades to keep the systems reliable before something goes down.
One mid-market employee shares the story of a server closet that her company had in a previous workplace. For starters, it could be accessed by nearly every employee of the company. She recounted that the IT department placed portable dehumidifiers in the room to keep moisture down. The IT department’s regular practice was to empty the server closet dehumidifiers in the office’s kitchen sink. Unfortunately, a new IT employee happened to trip while carrying one of the dehumidifiers and spilled water all over the server room. Every employee of the company was affected—they found out that the work they had done since the last backup, which happened to be 5 days ago, had disappeared. Even worse, their servers were down for several days after the incident, further impacting their daily business operations.
Although in the past, people feared that cloud would not be secure, or a company would lose control over its data—cloud has proven to be more secure than on-premises hardware. First, cloud vendors host their own data centers and because this is their main business, they have cutting-edge climate control environments to protect their clients’ data. Cloud vendors adhere to frequent hardware replacement turn-over schedules to keep uptime maximized and cloud operations state-of-the-art. Cloud vendors monitor their data centers 24/7/365, are security experts, and have strict controls in place in order to service clients in highly regulated industries with rigorous data security needs. For most mid-sized businesses, it is more cost effective to rely upon the expertise of a cloud vendor for data security and uptime than to host and maintain its own servers, stay on top of the latest security threats, and staff its data center (or data closet) for monitoring to prevent downtime and security breaches.
Large enterprises often can afford to build their own data centers providing them an alternative to an external cloud provider. However, this is incredibly expensive and can set organizations back by USD $10-25 million on yearly setup and operation costs. This infrastructure also takes a lot of time to be implemented and in today’s fast-paced business environment, this might not be entirely acceptable for decision-makers.
Yet, even for enterprises, on-premises solutions no longer make the most sense. Most modern business applications are cloud-native. Cutting-edge data analytics solutions are cloud-native and connect and integrate data sources using cloud technologies. Clouds are better suited for analytics than on-premises hardware, due to scalability and ability to absorb compute spikes (instead of having to invest in hardware with capacity for compute spikes as machine learning algorithms converge—which leads to excess capacity at other times).
According to Insights for Professionals, 63% of senior IT leaders and company executives who were surveyed expected to invest in cloud infrastructure-as-a-service in 2022. Considering the state of on-premises servers, which are becoming an obsolete technology that require an IT department to keep a constant eye on it, cloud technology is a natural progression in infrastructure for better data management. Gartner reports by 2025 almost 85% of companies will have moved to a cloud-first approach. Cloud technology has now evolved to a point where it provides better stability and security at a more economical price than on-premises solutions.
Mid-Market Company Considerations
Many organizations are operating in hybrid and multi-cloud environments. This means that they have some data in on-site servers, some data in cloud based line of business applications (relying on the application provider for data storage in whichever cloud the application vendor uses for its product), and many have some data in a public cloud.
However, mid-market companies have added considerations when choosing a cloud solution. Most public cloud service providers do not offer data management services. You need to do this yourself. Yet, mid-market companies often do not have this expert talent in-house. For success, mid-market companies need a cloud hyper-scaler that also provides data engineering services to build data connectors and pipelines, warehouses, data lakes, and the like. This skill set is different from a typical IT employee. Hyper-scalers—who can help organizations with data management, transform data from disparate sources into a decision and analytics-ready status, and bring transactional data into the forefront using a cost-effective cloud solution—tend to be private cloud vendors. For this reason, private cloud solutions make more sense than public cloud for mid-sized organizations.
A side-by-side partnership with an experienced cloud-native data platform company will have a measurable and positive impact on mid-market company data management strategies, with built-in access to technical resources and experts, so that your company does not need to hire new FTEs to support data management. Rely on the data management companies for data management so that your company can focus on your main line of business.
Aunalytics’ high performance private cloud provides a highly redundant and scalable platform for hosting servers, data, analytics, and applications at any performance level. Aunalytics delivers data management in a side-by-side service model, bringing companies the technology and the talent needed for data management success. To learn more about our Enterprise Cloud solution, click here.
Does Your Mid-Market Firm Have the Right Talent to Maximize Its Data Tech Investments?
Does Your Mid-Market Firm Have the Right Talent to Maximize Its Data Tech Investments?
Investing in digital transformation technologies can be a waste of money if your company forgets one important point. That point is, no matter how cutting edge the tech or tool may be, people are needed with specific technical expertise in order to derive true business value from these investments.
Unlike large enterprises, mid-market companies often try to find this expertise in their IT manager, hoping a jack-of-all-trades approach will take care of it. This is an unfortunate mistake, since it would require the IT manager to have unusual command over a long laundry list of duties, from data integration, ingestion, and preparation to data security, regulatory compliance, data science, and building pipelines of data ready for executive reporting from multiple cloud and on-premises environments. This is not just a tall order for a mid-market IT manager to pull off, but likely an impossible one.
At the same time, it’s unreasonable to expect that most mid-market firms can hire an entire division of data experts—who each need to be highly compensated—in order to achieve the organization’s digital transformation goals. Even if a mid-market player could afford it—which is unlikely to make economic sense—these talent resources are scarce and in high demand.
If you’re still wondering whether your IT manager’s skill set, leveraged by your in-house IT technicians, can properly run the gamut required to achieve value from your data technology investments, consider that the person in this position would need the ability to master a wide range of skill sets, from cloud architecture, database engineering, and master data management to data quality, data profiling, and data cleansing. More specifically, your IT manager would need to take on five additional specialized roles for technical talent that are critical for achieving value from data technology investments.
These roles are:
Chief Data Officer/Chief Digital Officer
A chief data officer (CDO) is focused on—you got it—data. Most mid-market companies understandably don’t have a CDO, which means they don’t have anyone who assures regulatory compliance for data handling while managing and exploiting information assets, reducing uncertainty and risk, and applying data and analytics to drive cost optimization and revenue objectives. For IT managers to fulfill a CDO role, they’d have to be equipped to bring a global perspective to company data, help their organization gain competitive advantage over peers, and manage data and analytics. They’d also need the ability to secure data, transform it into valuable business information, lead digital transformation initiatives, and use data for growth and operational efficiency.
Cloud Engineer
The primary job of a cloud engineer is to keep cloud data centers operational and secure for ecosystem users to be able to store and access their data. Cloud engineers are experts in minimizing downtime, managing access to data, managing compute and storage, and setting up cloud architectures for clients, tenants, and containers. They also monitor data center hardware, servers, networks, and communications systems for operational continuity and efficiency.
Data Security Expert
Mid-market firms also need a way to channel the talents of a data security expert, CISO, or cybersecurity director to ensure cyber-security for the company’s data. Data security experts must keep current on emerging threats while executing data security strategies to fend off and remediate attacks. This involves a wide range of duties, including working closely with the IT team to run the company’s Security Operations Center (SOC), constantly monitoring servers, networks, and workstations for security threats, and staying up to date on the changing compliance laws and regulations for the business, to name a few. While larger IT teams have bandwidth to fill cybersecurity needs inhouse, many midmarket IT teams do not have capacity for the 24/7/365 monitoring and security edits needed to thwart attacks, let alone bandwidth for executing on mitigation and response strategies needed to overcome them.
Data Engineer
A data engineer’s primary job is to prepare data for analysis or operational uses, which involves integrating data from different sources, as well as implementing and executing data profiling, cleansing, transforming, and normalizing data. Data engineers also work with data in motion and use master data management to ensure data consistency across an organization. Finally, a data engineer is your go-to technical resource for database construction and management, helping to optimize the company’s data ecosystem.
Data Scientist
It should be clear now why a mid-market IT manager should not be expected to take on these additional professional roles, but in case there’s any doubt, keep in mind that a data scientist is also needed. Data scientists develop algorithms and leverage deep learning models to analyze data with artificial intelligence and machine learning. The data scientist creates the “brain” of the data analytics solution to position it for providing accurate answers based on business information. Data scientists also mine data to find opportunities for business growth and efficiency. Ideally, the data scientist uses tools that enable non-technical business users to query data sets without having to write SQL or other code.
Master of One
If you’ve correctly determined that your mid-market IT department does not have enough time to absorb these data roles into their regular duties of keeping your company systems stable and responding to help desk tickets from your team, don’t despair. There’s a viable solution for mid-market businesses with this dilemma: they can partner with data experts who provide a side-by-side model coupling technology with talent. This allows the mid-market to efficiently compete, leveraging the necessary skillsets to achieve digital transformation success.
What does successful mid-market digital transformation require? The key is to have a cloud-based data center, a cloud native data management platform, and cloud native analytics, thus shifting the burden of procuring and maintaining the infrastructure to a third-party vendor in the data industry. Instead of attempting to reinvent the wheel in house, mid-market players should ensure they’re partnered with the right infrastructure to maximize the data-center capabilities, and data storage and management, for effective digital transformation.
Mid-market firms can gain the benefits of working with a wide range of experts including cloud engineers, data engineers, security experts, data scientists, and other highly skilled technical resources if they establish a partnership with a data platform company. By opting for this type of side-by-side expert help, the mid-market can achieve true business value—without needing to hire an entire data team.
Bridging the Mid-Market Talent Gap for Digital Transformation
Bridging the Mid-Market Talent Gap for Digital Transformation
To achieve business value from data technology investments, mid-market companies need the right technical expertise and talent. Yet many mid-market firms push this onto their IT manager, assuming that since it is technology related, IT has it. This is a mistake because most IT departments do not have time for data analytics. They are busy full time keeping company systems stable and secure, and providing support to your team members. This by necessity results in IT deprioritizing data queries over crucial cybersecurity attack prevention. Business analysts and executives get frustrated waiting for data query results, and the data is stale or the business opportunity has passed by the time query results are in.
But even if your IT team had time for it, it still is a mistake to rely on traditional technology administrators for data analytics success. This is unless your IT department has expertise across a wide range of skill sets, from cloud architecture, database engineering, master data management, data quality, data profiling, and data cleansing. What’s more, your IT manager would need to have command over data integration, data ingestion, data preparation, data security, regulatory compliance, data science, and building pipelines of data ready for executive reporting from multiple cloud and on premises environments.
When you read this laundry list of needs, it becomes clear that most mid-market IT departments lack the specialized experts needed to derive business value from their data. Unlike larger enterprises that have the resources to hire skilled staff for these roles, the mid midsize organization requires another option that provides access to the right tools, resources, and support. One that integrates, enriches and is trained in utilizing AI, machine learning, and predictive analytics to achieve more useful results.
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Bridging the Mid-Market Talent Gap for Digital Transformation
Bridging the Mid-Market Talent Gap for Digital Transformation
To achieve business value from data technology investments, mid-market companies need the right technical expertise and talent. Yet many mid-market firms push this onto their IT manager, assuming that since it is technology related, IT has it. This is a mistake because most IT departments do not have time for data analytics. They are busy full time keeping company systems stable and secure, and providing support to your team members. This by necessity results in IT deprioritizing data queries over crucial cybersecurity attack prevention. Business analysts and executives get frustrated waiting for data query results, and the data is stale or the business opportunity has passed by the time query results are in.
But even if your IT team had time for it, it still is a mistake to rely on traditional technology administrators for data analytics success. This is unless your IT department has expertise across a wide range of skill sets, from cloud architecture, database engineering, master data management, data quality, data profiling, and data cleansing. What’s more, your IT manager would need to have command over data integration, data ingestion, data preparation, data security, regulatory compliance, data science, and building pipelines of data ready for executive reporting from multiple cloud and on premises environments.
When you read this laundry list of needs, it becomes clear that most mid-market IT departments lack the specialized experts needed to derive business value from their data. Unlike larger enterprises that have the resources to hire skilled staff for these roles, the midsize organization requires another option that provides access to the right tools, resources, and support. One that integrates, enriches and is trained in utilizing AI, machine learning, and predictive analytics to achieve more useful results.
Achieving Digital Transformation
Digital transformation has been defined by some as the integration of digital technology into all areas of a business, fundamentally changing how employees operate and deliver value to customers. Some of the challenges midsize businesses have with building an internal team to initiate this concept are employee pushback, lack of expertise to lead digitization initiatives, improper organizational structure, the absence of a digitization strategy and limited budget. As an alternative to building an internal operation, a more efficient way for mid-market businesses is to leverage the skillsets of experts by partnering with a consolidated group of experts, leveraging a side-by-side model that couples technology with talent. Look for solution providers that offer the following:
- Powerful cloud data centers paired with engineers skilled in architecting cloud-based applications and processes that better serve critical business requirements. These data centers are optimized for true multi-tenancy, built on seamlessly integrated hardware and software, offer business-driven configurability, world-class security and performant systems.
- Active Monitoring and Thoroughly Integrated Security. Monitoring and security should be pervasive across system infrastructure to defend against cyberattacks and provide remediation when required. Business customers will also expect full-time monitoring and on-demand help desk to address unexpected events. The data management platform underpinning applications should be monitored by experienced data engineers with success in building data warehouses, data lakes, and data pipes. They should also be able to integrate, cleanse, and transform data into decision-ready and analytics-ready business information.
- High ROI Business Insights that Drive Results. Data analytics investments need to provide real business value by giving actionable insights and finding opportunities within your data. With this in mind, data analytics should include access to data scientists and business analysts versed in your industry. These experts should be equipped to design AI-powered algorithms that answer the most pressing questions based on real-world business challenges.
Mid-Market Data Transformation for Enterprise-Class Results
Ensuring the right mix of hardware, software and resulting services are available to maximize the data center capabilities—and their ability to manage and protect data—is crucial to effective mid-market digital transformation. To compete and drive value, the cloud data center provider must deliver at all levels, with customizable business intelligence solutions powered by an effective data management platform that is secure and compliant. Successful mid-market digital transformation thus requires a shift of responsibilities for infrastructure procurement and maintenance to a third-party provider backed by experienced staff and best-in-class infrastructure.
When implementing a digital transformation project, your company gains from the many benefits this brings, such as a higher return on your IT investment, increased employee and customer experience, and greater business agility. This is further enhanced by leveraging experienced cloud engineers, data engineers, security experts, data scientists, and other highly skilled technical resources—achieving true business value from the investment. And by partnering with experts, your company’s time, resources, and innovation can be focused on its core competencies.
Top 3 Actions for CIOs to Take Now in a Recession Economy - PDF
Top 3 Actions for CIOs to Take Now in a Recession Economy
The current economy poses a triple threat for business: persistent high inflation; scarce expensive talent; and global supply constraints. However, there are 3 actions CIOs should take to play offense to emerge from a recession on top.
4 Questions Mid-market Companies Should Ask Themselves About Data Protection
4 Questions Mid-market Companies Should Ask Themselves About Data Protection
When the working world went remote due to the COVID-19 pandemic, many never returned to the office. This created new data-security challenges for many businesses, with an increasing amount of sensitive data now being stowed in the cloud, and workers continuing to access company data from off-site locations.
How safe is cloud security, which now often relies on “zero trust” security principles based on a user’s location rather than user credentials? While some worry that cloud security is less reliable than on-premise security, that’s not actually the case, particularly for mid-market businesses. The fact is that your data is actually more secure in a remote data center managed by security experts than by your in-house IT team.
You may feel a false sense of security by having your IT department guard your servers in a closet — but this strategy is extremely risky when it comes to data protection. It’s not standard for mid-market IT departments to possess expert skills in cloud security and data security, which are needed to properly safeguard data. Many mid-market companies, particularly those not in highly regulated industries, do not currently have Security Operations Centers.
