The school year is underway, and Backup School with ISG is back! Join ISG and Veeam as we educate our clients and their organizations about how they can keep their business up and running and eliminate downtime – even when the unexpected happens.
Is downtime simply an unacceptable thing in your mind? Then this webinar is for you. Go beyond backup to better understand business continuity.
The school year is underway, and Backup School is back! Together, ISG and Veeam focus on educating our clients and their organizations about how they can keep their business up and running and eliminate downtime – even when the unexpected happens.
Office 365 is a powerful suite of products – but it lacks a comprehensive backup of some of your most critical data. Learn how to protect yourself in this webinar.
The digital revolution has brought a host of new opportunity and challenges for enterprises in every sector of business. While some organizations have embraced the wave of change and made efforts to be at its forefront, others have held back. These institutions may not have sufficient staff to implement the changes or may be waiting for a proven added-value proposition.
In other words: No technology upgrades until the innovation is proven useful. There is some wisdom in this caution. Several reports have noticed that productivity and efficiency are not rising at expected levels alongside this technology boom. However, as Project Syndicate noted, this lag may be a case of outgrowing the traditional productivity model, meaning that not every employee action is measured in the old system.
However, there is another reason to explain why more technology does not automatically equal greater efficiency and higher profits. If a company buys some new software, it will see a minor boost. However, it will reap the full rewards only if staff properly learn to use said platforms.
Part of this problem stems from the misunderstanding that technology can only improve current work processes. This is not true. When looking at a basic enterprise operation like data visualization, technology has created an entirely new workflow.
Examining the traditional business model
In the traditional business model, all data visualization was manual. Employees would gather data from various endpoints and then input it into a visual model. Common examples of this process included pie charts and bar graphs. The employee would then present the data to the executive, who would use it to make information-based decisions.
While acceptable, this process is far from optimized. Most data had to be generated in spreadsheets before it was collected, using formulas made by staff. Collecting and framing the information is a time-consuming process that will absorb at least one individual. As employees are involved at every step of this workflow, there is a potential for human error.
The time involved prevented companies from acting on real time information. In the interim, intuition and "gut feeling" were used as substitutes for data-backed decisions. The people involved raised the level of risk that the data in question may be inaccurate or misleading.
Unlocking data analytics
Of course, with the arrival of the internet of things, companies have a lot more data collection at their disposal. Connected devices have provided a whole new network of information. This gold mine, also known as big data, has one downside: There is too much of it. A human cannot hope to categorize and analyze the information in any acceptable timeframe.
Enter data analytics. Using advanced technology like machine learning, companies can create and implement this software to study their data, creating automatic visualizations based on trends and prevalent patterns. According to Fingent, these software solutions employ mining algorithms to filter out irrelevant information, focusing instead on only what is important.
However, companies cannot simply go from a traditional system to a fully fledged data analytics solution for one reason: data segmentation. Many enterprises divide their information based on different departments and specializations. Each group works internally, communicating primarily with itself. While this method is helpful for organization, it greatly impedes data analytics potential.
If companies have siloed their data, the program will have to reach into every source, work with every relevant software and bypass every network design. In short, it will have to work harder to communicate. While modern data analytics solutions are "smart," they cannot navigate barriers like this easily. They are designed to optimally read only the information that is readily available.
For organizations to fully capitalize on the potential of internal data analytics, infrastructure overhaul is needed. Departments – or at least their data – must be able to freely communicate with one another. This process entails implementing a common software solution that is in use across the entire company.
The good news is that many modern solutions fit this need. Solutions like cloud platforms store relevant data in accessible locations and train employees to not segment their work. By creating an infrastructure that is open to the data analytics program, organizations can start to act on information, rather than relying solely on their gut.
Almost everyone, regardless of industry, recognizes the growing importance of cybersecurity. Cyberattacks are on the rise and growing increasingly varied and sophisticated. According to data collected by Cybersecurity Ventures, the annual cost of cybercrime is estimated to reach roughly $6 trillion by 2021. An effective information security policy is, in many cases, the only thing standing between companies and possible financial ruin.
The danger is especially real for small- to medium-sized businesses. Data from the U.S. Securities and Exchange Commission found that only slightly more than a third of SMBs (40 percent) survive for longer than six months after a successful data breach. For these types of organizations, cybersecurity is literally a matter of life and death.
The good news: Many businesses recognize the need for effective cybersecurity strategies and are investing heavily in personnel and software solutions. The bad news: Many of these same companies are only reacting, not thinking about how to best deploy this protective framework. Effective cybersecurity isn’t as simple as applying a bandage to a cut.
It can be better equated to introducing a new nutritional supplement to the diet. The whole procedure is vastly more effective if integrated into every meal. To best use modern cybersecurity practices, businesses must rethink their approaches to corporate data structure. Data analytics is a vital tool in providing the best in information protection.
“Segmenting data spells disaster for an effective cybersecurity policy.”
Siloed data is unread data
As organizations grow, there is a tendency to segment. New branches develop, managers are appointed to oversee departments – in general, these groups tend to work on their projects and trust that other arenas of the company are also doing their jobs. The responsibility is divided and thus, easier to handle.
While this setup may make the day-to-day routine of the business easier on executives, it spells disaster for an effective cybersecurity policy. This division process creates siloed or segmented data pools. While a department may be very aware of what it is doing, it has far less knowledge of other corporate branches.
Many organizations may figure that an in-house IT team or chief information security officer can oversee everything, keeping the company running at full-tilt. However, this assumption is only half-true. While these staff members can and do oversee the vast majority of business operations, they will lack the data to make comprehensive decisions. A report from the Ponemon Institute found that 70 percent of cybersecurity decision-makers felt they couldn’t effectively act because of a surplus of jumbled, incoherent data.
Data analytics, or the study of (typically big) data, provides facts behind reasoning. To gather this information, companies need systems and software that talk to one another. Having the best-rated cybersecurity software won’t make a difference if it can’t easily communicate with the company’s primary OS or reach data from several remote branches.
CISOs or other qualified individuals can make practical, often less-expensive strategies with a clear view of the entire company. Without this type of solution, a business, no matter its resources or personnel, will essentially be operating its cybersecurity strategy through guesswork.
Centralized businesses may miss real-time updates
Businesses face another challenge as they expand. Data collection has, in the past, slowed with remote locations. Before IoT and Industry 4.0, organizations were bound with paper and email communications. Remote branches typically grouped data reports into weeks or, more likely, months.
This approach meant that the central location effectively made decisions with month-old information. When it comes to minimizing the damage from data breaches, every hour matters. Luckily, many institutions can now provide data streaming in real time. Those that can’t must prioritize improving information flow immediately. Cybercrime looks for the weakest aspect within a company and tries to exploit the deficiency.
For data analytics to work properly, businesses need access to the full breadth of internal data. The more consistent and up to date this information is, the better CISOs and IT departments can make coherent and sensible decisions.
Visibility may not sound like the answer to fighting cyberattacks, but it is a crucial component. Companies need to be able to look within and adapt at a moment’s notice. This strategy requires not just the ability to see but also the power to make quick, actionable adjustments. Those organizations that still segment data will find this procedure difficult and time consuming.
As cybercrime becomes an expected aspect of business operations, those who still think in siloed brackets must change their mindsets or face expensive consequences.
Over the last decade, many companies have been shifting IT responsibilities to the cloud, a solution that allows various users and hardware to share data over vast distances. Cloud programs frequently take the form of infrastructure as a service. A company that can't afford in-house servers or a full-sized IT team can use cloud solutions to replace these hardware and personnel limitations.
Large companies like Amazon, Microsoft and Google are all behind cloud services, propelling the space forward and innovating constantly. However, there are still limitations when it comes to cloud adoption. For as convenient as theses services are, they are designed for ubiquitous usage. Organizations that specialize in certain tasks may find a cloud solution limited in its capabilities.
Those businesses wishing to support service-oriented architecture may wish to consider a hybrid cloud solution, a new service becoming widespread throughout various enterprise application. As its name suggests, a hybrid cloud solution combines the power of a third-party cloud provider with the versatility of in-house software. While this sounds like an all-around positive, these solutions are not for every organization.
"Before businesses discuss a hybrid solution, they need three separate components."
Why technical prowess matters for hybrid cloud adoption
TechTarget listed three essentials for any company attempting to implement a hybrid cloud solution. Organizations must:
- Have on-premise private cloud hardware, including servers, or else a signed agreement with a private cloud provider.
- Support a strong and stable wide area network connection.
- Have purchased an agreement with a public cloud platform such as AWS, Azure or Google Cloud.
Essentially, before businesses can discuss a hybrid solution, they need all the separate components. An office with its own server room will still struggle with a hybrid cloud solution if its WAN cannot reliably link the private system with the third party cloud provider. And here is the crutch. Companies without skilled IT staffs need to think long and hard about what that connection would entail.
Compatibility is a crucial issue. Businesses can have the most sophisticated, tailored in-house cloud solution in the world but, if it doesn't work with the desired third party cloud software, the application will be next to useless. It isn't just a matter of software. Before a hybrid cloud solution can be considered feasible, equipment like servers, load balancers and a local area network all need to be examined to see how well they will function with the proposed solution.
After this preparation is complete, organizations will need to create a hypervisor to maintain virtual machine functionality. Once this is accomplished, a private cloud software layer will be needed to empower many essential cloud capabilities. Then the whole interface will need to be reworked with the average user in mind to create a seamless experience.
In short: in-house, skilled IT staff are essential to successfully utilizing a hybrid cloud solution. If businesses doubt the capabilities of any department, or question whether they have enough personnel to begin with, it may be better to hold off on hybrid cloud adoption.
Without being properly installed, a poorly implemented solution could cause delays, lost data and, worse of all, potentially disastrous network data breaches.
The potential benefits of the hybrid cloud
However, if created the right way, a hybrid cloud solution brings a wide array of advantages to many enterprises, particularly those working with big data. According to the Harvard Business Review, hybrid cloud platforms can bring the best of both solutions, including unified visibility into resource utilization. This improved overview will empower companies to track precisely which employees are using what and for how long. Workload analysis reports and cost optimization will ultimately be improved as organizations can better direct internal resources and prioritize workers with stronger performances.
Overall platform features and computing needs will also be fully visible, allowing businesses to scale with greater flexibility. This is especially helpful for enterprises that see "rush periods" near the end of quarter/year. As the need rises, the solution can flex right along with it.
Hybrid cloud services are also easier to manage. If implemented properly, IT teams can harmonize the two infrastructures into one consistent interface. This will mean that employees only need to become familiar with one system, rather than learning different apps individually.
Companies processing big data can segment processing needs, according to the TechTarget report. Information like accumulated sales, test and business data can be retained privately while the third party solution runs analytical models, which can scale larger data collections without compromising in-office network performance.
As The Practical Guide to Hybrid Cloud Computing noted, this type of solution allows businesses to tailor their capabilities and services in a way that directly aligns with desired company objectives, all while ensuring that such goals remain within budget.
Organizations with skilled, fully formed IT teams should consider hybrid cloud solutions. While not every agency needs this specialized, flexible data infrastructure, many businesses stand ready to reap considerable rewards from the hybrid cloud.
Companies that backup to tape as their offsite backup often aren’t aware of what recovering from tape looks like until they unfortunately have to live through it. Depending on the nature of the failure and the extent of the data involved, that type of recovery can take days to restore “business as usual” functionality.
What Backup Is… and What It Isn’t
- Backup is for data protection and targeted item recovery:
It is not for archive. Archives ideally will be indexed for search, have a managed retention policy, and will be stored on less expensive storage mediums.
- It is not for disaster recovery. It is nearly impossible to test a full environment recovery scenario when relying on this method. It will often require 100% more equipment overhead to have the empty equipment in standby, equipment not providing any usefulness or return on investment
- It is not a failover solution. Recovery times with this method should be measured in weeks, not hours.
Snapshots are not backup:
- Snapshots can be used as one part of a backup strategy, but provide no protection on their own in scenarios where the storage devices have failed or are no longer available
- Snapshots are usually not very granular and are commonly the recovery method of last resort
- Snapshots are not disaster recovery on their own, only a part of a comprehensive plan
The untested data recovery plan is both useless and a waste of time to create:
- Make time for testing, it will always be worth it.
- Do not let the single point of failure be a human, involve many members of the team in the process so that when the time comes to execute your plan it does not have to wait for the only one who knows how.