Tag: Storage

Technology contained

Over the past decade container technology has become a popular method for packaging applications in an effective way. Some developers believe is better than that offered by virtual machines and other technologies.

Container technology has been embraced by the big cloud computing providers including Microsoft Azure, Amazon Web Services, and Google’s Cloud platform.

Examples of the actual container software include the Apache Mesos, Docker, rkt (pronounced rocket), and Kubernetes.

But what is container technology?

Logically, it gets its name from shipping. Shipping containers standardize how goods are moved around. Goods get placed in steel shipping containers which can be picked up by cranes and fit into ships. They tend to have standard sizes.

By standardizing the process and keeping the items together, your container can be moved as a unit and it costs less to do it this way.

In computer terms, container technology is referred to as just a container: a method to package your applications so they can be run, with their dependencies, isolated from other processes.

Container technology decreases the potential for problems when developers move programs from server to server before the program is in a state where it is saleable.

When you use container technology to create an application, you can code everything using just one operating system and database. This makes the application quite easy to replicate as resources including memory and the central processing unit (CPU) are shared. This also makes your technology great for scaling and for working within the cloud.

Out with the old…

If you don’t use container technology, you can have a situation where a program runs well on one machine but has problems on your server. This common problem occurs when you move a program from a data server to a cloud server.

Many issues can happen because of variations in machine environments. These include differences between your operating system, secure sockets layer libraries, storage, and network topology.

So, computer container technology picks up all of your software and related parts which include dependencies, being libraries, binaries, and configuration files. They all get migrated as a unit, avoiding the differences between machines including operating system differences. This will also include underlying hardware that leads to incompatibilities and crashes.

And, importantly, containers also facilitate the deployment of your software to your server. Advocates of using container technology say it is a much better tech to use than that which preceded it – virtual machines.

In this case, one physical server would be used for multiple applications through visualization technology. Each virtual machine contains the entire operating system, as well as the application to run.

The physical server then runs several virtual machines, each with its own operating system, with a single hypervisor emulation layer on top. By running several operating systems simultaneously, you incur a lot of overheads on your server as resources get used.

…and in with the new

Container technology allows your server to run a single operating system because each container can share that system.

The parts of your operating system that are shared are read-only to not interfere with the other containers. Therefore, compared with virtual machines, containers require fewer resources of the server, and are much more efficient.

You can pack many more containers onto a single server. Each virtual machine may require you to have gigabytes of storage. But each container running a similar program may only need megabytes.

How do the containers operate?

Containers are set up in an architecture known as a container cluster. Then, in a container cluster, there is a single cluster master, with the other related containers set as nodes, that are your multiple worker machines. The cluster master schedules the workloads for your nodes, and also to manage their lifecycle, and their upgrades.

Containers allow programs to be broken down into smaller pieces, which are known as microservices.

A major advantage of having a program as component microservices is that different teams can work on each of the containers separately as long as the interactions between the different containers are maintained. This facilitates faster software development.

Containers are also flexible and can be orchestrated. Since the operating system would be already running your server, a container can be started and stopped in just a few seconds.

Some containers within architecture can be turned on during peak demand, and turned down when not needed.
The software can control this type of orchestration, and distribute the tasks among the container cluster.

The way forward with the tech

But is container technology overrated? Some people are concerned about the security around it.

Because multiple containers share the same operating system, there are growing concerns that container technology is less secure than virtual machines. If there is a security flaw in your host kernel it will affect your multiple containers.

Other software is being used to have more secure container technology. The use of isolated containers is, therefore, being constantly improved.

8 July 2020
Cloud-hosted services square up

Running your business requires choosing the right tools for you and your employees. In order to streamline work-related productivity, many organizations are migrating to cloud-based office suites. Specifically, Microsoft’s Office 365 and Google’s GSuite (now known as Google Workspace).

Both products boast a variety of helpful productivity tools and the latest remote collaboration technologies. While it’s impossible to say which one is “better”. This head-to-head comparison can help you decide which office suite is a better fit for your business.

What is Workspace & Office 365?

Office 365 and Workspace (previously GSuite) are packages, of powerful business tools that facilitate your day-to-day tasks using the cloud. They even provide business emails along with apps for creating documents, spreadsheets, presentations, video conference calls, shared calendars, and notes.

In addition, storing information on Google or Microsoft servers, rather than your own via these suites, can also save your business a lot of money.

Plans and Pricing

First, let’s look at plans and prices. It’s important to note that Microsoft requires an annual commitment, while Google offers you the option to make monthly payments if you prefer.

Contact us to get a formal quote for your business

Cloud packages head-to-head

Email

While both Office 365 and Workspace offer web and mobile apps (Outlook and Gmail, respectively) for email. There are, however, some subtle differences.

One advantage to Office 365 is the desktop version of Outlook, which is incredibly feature-rich and lets you sort and group emails with ease. Gmail, on the other hand, is widely used throughout the world. For this reason, a variety of third-party app options (e.g. WordPress) can be linked to it to enhance its capabilities.

Cloud Data Storage

For the entry-level plans, Office 365 Business Essentials wins out with 1 TB (terabyte) of storage per user, while the Workspace ‘Basic’ plan only offers 30 GB. GSuite includes emails in this storage limit, whereas Office 365 provides extra storage for email files with added archiving.

However, Workspace’s upgraded plans beat out most of Microsoft’s storage offerings. So long as your business has more than five employees, Workspace Business and Enterprise provides unlimited cloud storage. Although, businesses with less than 5 employees on the “Business” plan are capped at 1 TB. Only Microsoft’s E3 plan and higher offer the same unlimited cloud storage.

Applications

Applications are the cornerstones of a suite’s functionality. Workspace and Office 365 offer you a variety of comparable apps for word processing, creating spreadsheets and presentations, all on the cloud!

This means every user gets a free desktop version of the Office suite (i.e. Microsoft Word, Excel) to download.

These feature-rich apps expand far beyond the capabilities of the mobile and online versions, and are available on every plan except the ‘Business Essentials’.

While both services offer mobile and online apps, one major benefit of Office 365 are its desktop applications.

Collaboration

These online applications make both suites ideal for remote collaboration. Microsoft Teams lets facilitate this with tools like real-time co-authoring, mentioning users by name and chat capabilities while working on OneDrive. Microsoft now lets you collaborate using its desktop apps, too, although the updates to shared files are a bit sluggish compared to its online apps.

Similarly, GSuite offers Hangouts for chats and Google Drive for real-time collaboration. Google’s online and mobile apps were created with cloud collaboration in mind, so some might find them a bit more user-friendly.

For remote meetings, GSuite and Office 365 both offer group video conference calls. If you plan on large-scale video conferences, then Office 365 offers far more for your money: most plans have a 250-participant limit, while the E3 plan increases to an astounding 10,000-person limit.

Meanwhile, GSuite’s Google Meet allows up to 25 participants on the “Basic” plan, 50 on the “Business” plan, and 100 on the “Enterprise” plan.

Security

Cloud services are running into a variety of security issues, and these suites are no exception.

A 2019 Barracuda Networks’ report found that a large percent of ATO (account takeover) attacks were targeted at Microsoft Office 365 accounts after businesses migrated emails to the service.

These attacks prompted the Cybersecurity and Infrastructure Security Agency (CISA) to issue a set of best practices. The aim was to help organizations migrate their email services while avoiding risks and vulnerabilities.

Meanwhile, Google recently announced that a cloud storage feature for encrypted passwords on its “Enterprise” plans was faulty. As a result, some user passwords were stored in plaintext on Google’s servers!

While cloud computing has its risks, the two suites do have impressive security features. GSuite is comparable to Google’s own level of security and offers AI detection of suspicious activity, Two-Factor authentication, and data leak protection—in which admins can block outgoing communication determined by set keywords.

On the other hand, Office 365 has the option of Multiple Factor Authentication (MFA), along with the detection of malware, viruses, and suspicious activities. Microsoft also provides data loss protection, and admins can restrict access to company-issued devices only.

Ease of Use

So, which is easier to use? Well, it depends on who you are, and your ability to grasp software quickly.

If you’re accustomed to working with MS Word or Excel documents, and edit them for work on a regular basis, then Office 365 and its desktop-to-online formatting compatibility will probably be your best bet. This is especially true if your company solely computes with Windows PCs.

However, new users might find GSuite apps easier to learn, as the tools are a bit simpler and straightforward.

So, which is best for you?

Firstly, Office 365 offers feature-rich apps, and most of its plans come with a desktop version of MS Office applications. This is a definite advantage over its competitors.

Its entry-level plan is far more generous in terms of data storage than GSuite’s “Basic” plan. In addition, businesses that already exclusively use Windows technology are likely to find Office 365 better-suited for their needs.

With that said, GSuite was originally designed as a cloud collaborative productivity tool. Therefore, its features might be easier for collaboration and can be used among a wider variety of Windows and Mac devices. In addition, GSuite’s Business’ plans and above outdoes Microsoft when it comes to unlimited cloud file storage. <- This has changed since the article was first published.

Unfortunately, I can’t tell you which of the two is “best.” But, with this knowledge in mind, you can make an informed decision to choose the best cloud suite for you.

3 June 2019
Impact of Automation on Business
We are living in exciting and innovative times with futuristic technology literally at our fingertips. But for the longest time, small to medium-sized businesses were not serviced by the latest tech trends enterprises have been able to benefit from.

That is, until now. This piece explores these technology trends and how they will impact business in 2018 and beyond.

So, what kind of things can this ‘smart’ tech do? Just 4 months ago, an AI machine managed to complete a University level math exam 12 times faster than it normally takes the average human.

How? Through the art of machine learning; where computers learn and adapt through the experience without explicitly being programmed.
Furthermore, Facebook made headlines earlier this year when their chatbots created their own language. Some ‘fake news’ stories claim that the engineer’s pulled the plugin a panic as they were getting too smart.

However, the truth is that for Facebook’s purposes the chatbots needed to stick to English rather than developing their own shorthand. Their machine learning chatbots did nevertheless, create their own language outside their explicit programming.

This evolving area of computer science is the future for service businesses, and it’s already affecting the way we live and work today. In fact, research firm

Markets and Markets estimate that the machine learning market will grow from $1.41 billion in 2017 to $8.81 billion by 2022!

So buckle up because these technology trends will affect every part of your business, from marketing to operations all the way through to payroll, and here’s how.

AI and Social Media Marketing

In April 2017, CRM software provider, Salesforce conducted a study of marketing leaders worldwide, and the results were mind-blowing. Respondents said they expect to see improvements in efficiency and advancements in personalization over the next five years.
More than 60 percent of marketers envision leveraging AI to create dynamic landing pages, websites, programmatic advertising and media buying.

AI will affect marketing by nurturing leads through social media. But how? Through personalized, real-time content targeting that produces 20 percent more sales opportunities.

With behavioural targeting methods, AI will be able to locate and start the nurturing process. For example, a marketing stack that employs AI algorithms might learn that a specific buyer who checks into LinkedIn on Monday mornings has recently started looking for a new CRM tool.

The software can then suggest (or even create) targeted posts to be published on the days and times that they’ll see them.

Currently, savvy marketers that are using social listening as a way to nurture leads don’t have the necessary enhancement of AI. This is, however, time-consuming, manual, and not in real-time.
So how do you start to get ready for this type of future content marketing distribution?

Firstly, you will need to have your buyer personas (using the consumer black box theory ) well defined. Taking a solid look at your CRM will give you tons of hints for content that will get qualified leads to respond.

By taking a step back and analyzing your channel’s content (like emails, phone calls, and social media messages) you will start to get the right kind of insights. The ones that will prompt a lead to take the next step into the second phase of your sales funnel.

For instance, a C-Suite executive might respond best to data-driven whitepapers and infographics to peak their interests, whereas a fellow marketer might be more suited for an interactive case-study or video.
The only way to get these kinds of insights is to do a deep dive into your CRM platform and conduct a thorough review of customer details – using semantic analysis to understand the level of buying intent behind the words your qualified prospects use.

Hot tip: Starting to run your analysis now and developing strong personas will be key to implementing AI algorithms to your social media in 2018 and beyond.

Marketing and Machine Learning

Put simply, machine learning is about understanding data and statistics. It’s a technical process where computer algorithms find patterns in data, then predict probable outcomes. An example is when your email determines whether a particular message is spam or not depending on words in the subject line, links included in the message, or patterns identified in a list of recipients.

It’s the perfect example of how machine learning can be applied in marketing to optimize for successful campaigns.

Businesses can also use machine learning to up-sell the right product, to the right customer, at the right time. In 2018, marketers will continue to rely on machine learning to understand open rates when it comes to email. This way, you know exactly when to send your next campaign to increase click-through rates and ROI.

The next big thing? It might sound small but ticket tagging and re-routing can be a massive expense for small businesses – costs that can be saved with machine learning.

Having a sales inquiry automatically end up with the sales team, or a complaint end up instantly in the customer service department’s queue, is going to save companies a lot of time and money, and this is all being made possible with modern technology.

Here’s what else to expect in 2018:

E-Commerce Reaches New Heights

You’ve been shopping for a new pair sunglasses on Amazon, then before you know it, your Facebook feed is filled with multiple eyewear ads and related trends for summer.
This is machine learning.
In fact, this example of analyzing data based on a user’s purchase history or online shopping behaviour is the future for e-commerce.

Retail companies are also tracking what ads or images you’re most likely to stop scrolling on, in order to target you with specific content. For example, if you always click on ads that contain happy women and some text, then a machine will log this as preferred content so that you are only targeted with ads that fit this description.

Machines can also track what time of day you are most active on Facebook, Instagram, Twitter, and/or Pinterest, in order to present these ads to you at an optimal buying time.

Then when it’s time to purchase, machine learning is applied to reduce the risk of credit fraud in small businesses.

How? Machines learn from historical datasets that contain fraudulent transactions and can identify patterns that represent a typical fraudulent transaction.
Similar to the way spam emails are detected and deterred. Machine learning will start to affect other parts of your business funnel as well, just take a look at the rise of Chatbots.

Integrating Chatbots

There was a time in which chatbots were only thought of as manmade pests on the Internet. Through machine learning, they are getting smarter and businesses are embracing them en mass.
In 2018 and beyond, chatbots will play a key role in the future of customer service. Why? Chatbots can help achieve a faster customer service resolution, as well as provide quick histories of each customer for impeccable customer service.

There are some key benefits that chatbots have over solely human interactions:
- Giving 24/7 customer service: The great things about machines? They don’t sleep! Coupled with the fact that chatbots are getting sophisticated enough to recognize human emotions such as anger, confusion, fear and joy. So should a chatbot encounter negative sentiments from the customer, they can seamlessly transfer to a human to take over and finish assisting the customer.
- The era of being ‘on hold’ is gone: A huge barrier to providing excellence in customer service is long wait times. How many times have you tried to get customer service from Comcast (or any TV/Internet provider) and you are getting progressively more frustrated with the wait times? This can all be eliminated with chatbots!
- Quick access to customer data makes service more personal: One thing that humans will never be better at than chatbots is quickly digesting customer data and history to provide context to customer questions.
- Chatbots excel at collecting customer data from support interactions. They can serve as virtual assistants that can feed customer data to your customer service officers so they have a full history of each account quickly.
The final trend we’ll explore is Automation and how it affects businesses today.

Automation now and beyond 2018

Though Machine Learning and AI are hot topics in the tech world, it is not to a point that small to medium-sized businesses can leverage them in the immediate future. But there is still hope for them with automation.
Powered by the Cloud, this type of technology has already revolutionized Marketing and Sales workflows and interactions but it is also starting to touch the various other parts of a business. For example:

Operations Automation

Once you win an important sale, you’ve got to deliver the product or service you’ve promised to the client. What does that process look like for most businesses now? You all will have a kick-off meeting and hope to cover all the promises that marketing and sales have given to your client.

However, with the use of operations automation and a powerful CRM, you will be able to read the interactions and see all the various touch points a client had with your company before that kick off call even happens.

This will give your service businesses a head start in providing great client relations and managing expectations. This category of SaaS products is called Service Operations Automation, or ServOps for short.

Accounting Automation

If there is one data-entry heavy department it would be Accounting. The problem is that as humans, we are fallible and much slower at data entry than a machine. Innovations with bank feeds, rules-based categorization and integrated payments have dramatically reduced the workload of clerical and bookkeeping staff.

This gives business owners more timely access to accurate financial information for their businesses.

Research, done by Xero, (a popular financial software provider) suggests that by 2020, automation will be commonplace in accounting. A significant number of finance professionals will be using the next level of analytical tools to help them add value to business models across the globe.

Payroll/HR Automation

Finally, the Cloud and Automation have come to the Payroll and Human Resources sector. These important areas of a business too often suffer because small businesses aren’t big enough to afford a full-time HR department.

What’s the alternative? Having only part-time efforts of founders and principals which can often lead to serious risk to the business.

With new automation technology, compliance is automated by platforms. The effort of keeping time-off approvals in sync with PTO balances and payslips becomes a thing of the past.

In the near future, we will see the rise of great technology, powered by the Cloud, Automation, AI, and Machine Learning.

This truly is the start of the Golden Age of Information Technology and it is time for businesses to take a hard look at their organizations and find ways to start integrating these tech trends.

This is a slightly shortened re-blog from a marketing post on Tenfold.com *

*This post was guest-authored by Tara Callinan and Jenneva Vargas from Accelo
23 July 2018
The Impact of AI, Machine Learning & Automation on Businesses
We are living in exciting and innovative times with futuristic technology literally at our fingertips. But for the longest time, small to medium-sized businesses were not serviced by the latest tech trends enterprises have been able to benefit from. That is, until now. This piece explores these technology trends and how they will impact business in 2018 and beyond.

So, what kind of things can this ‘smart’ tech do? Just 4 months ago, an AI machine managed to complete a University level math exam 12 times faster than it normally takes the average human. How? Through the art of machine learning; where computers learn and adapt through the experience without explicitly being programmed.

Furthermore, Facebook made headlines earlier this year when their chatbots created their own language. Some Fake News stories claim that the engineer’s pulled the plugin a panic as they were getting too smart. However, the truth is that for Facebook’s purposes the chatbots needed to stick to English rather than developing their own shorthand. Their machine learning chatbots did nevertheless, create their own language outside their explicit programming.

This evolving area of computer science is the future for service businesses, and it’s already affecting the way we live and work today. In fact, research firm Markets and Markets estimates that the machine learning market will grow from $1.41 billion in 2017 to $8.81 billion by 2022!

So buckle up because these technology trends will affect every part of your business, from marketing to operations all the way through to payroll and here’s how.

Marketing Gets Smarter with AI and Machine Learning

AI and Social Media Marketing

In April 2017, CRM software provider, Salesforce conducted a study of marketing leaders worldwide, and the results were mind-blowing. Respondents said they expect to see improvements in efficiency and advancements in personalization over the next five years. More than 60 percent of marketers also envision leveraging AI to create dynamic landing pages, websites, programmatic advertising and media buying.

The main way AI will affect marketing is through nurturing leads through social media. But how? Through personalized, real-time content targeting that produces 20 percent more sales opportunities. With behavioural targeting methods, AI will be able to locate and start the nurture process, for example, a marketing stack that employs AI algorithms might learn that a specific buyer who checks into LinkedIn on Monday mornings has recently started looking for a new CRM tool. The software can then suggest (or even create) targeted posts to be published on the days and times that they’ll see them: one that asks their requirements of the software and another follow up piece with a comparison of the CRM ecosystem.

Currently, savvy marketers that are using social listening as way to nurture leads don’t have the necessary enhancement of AI and is, therefore, time-consuming, manual and not in real-time. So how do you start to get ready for this type of future content marketing distribution?

Firstly, you will need to have your buyer personas (using the consumer black box theory ) well defined. Taking a solid look at your CRM will give you tons of hints for content that will get qualified leads to respond. By taking a step back and analyzing your channel’s content (like emails, phone calls and social media messages) you will start to get the right kind of insights that will prompt a lead to take the next step into the second phase of your sales funnel. For instance, a C-Suite executive might respond best to data-driven whitepapers and infographics to peak their interests, whereas a fellow marketer might be more suited for an interactive case-study or video.

The only way to get these kinds of insights is to do a deep dive into your CRM platform and conduct a thorough review of customer details – using semantic analysis to understand the level of buying intent behind the words your qualified prospects use.

Hot tip: Starting to run your analysis now and developing strong personas will be key to implementing AI algorithms to your social media in 2018 and beyond.

Marketing and Machine Learning

Put simply, machine learning is about understanding data and statistics. It’s a technical process where computer algorithms find patterns in data, then predict probable outcomes – like when your email determines whether a particular message is spam or not depending on words in the subject line, links included in the message, or patterns identified in a list of recipients. This is a perfect example of how machine learning can be applied in marketing to optimize for successful campaigns.

Businesses can also use machine learning to up-sell the right product, to the right customer, at the right time. In 2018, marketers will continue to rely on machine learning to understand open rates when it comes to email – so you know exactly when to send your next campaign to increase click-through rates and ROI. The next big thing? It might sound small but ticket tagging and re-routing can be a massive expense for small businesses – costs that can be saved with machine learning.

Having a sales inquiry automatically end up with the sales team, or a complaint end up instantly in the customer service department’s queue, is going to save companies a lot of time and money, and this is all being made possible with modern technology.

And while solving issues in record time and delivering successful email campaigns is great, this is just the beginning.

Here’s what else to expect in 2018:

E-Commerce Reaches New Heights

You’ve been shopping for a new pair sunglasses on Amazon, then before you know it, your Facebook feed is filled with multiple eyewear ads and related trends for summer: this is machine learning. In fact, this example of analyzing data based on a user’s purchase history or online shopping behaviour is the future for e-commerce.

Retail companies are also tracking what ads or images you’re most likely to stop scrolling on, in order to target you with specific content. For example, if you always click on ads that contain happy women and some text, then a machine will log this as preferred content so that you are only targeted with ads that fit this description. Machines can also track what time of day you are most active on Facebook, Instagram, Twitter and/or Pinterest, in order to present these ads to you at an optimal buying time.

Then when it’s time to purchase, machine learning is applied to reduce the risk of credit fraud in small businesses. How? Machines learn from historical datasets that contain fraudulent transactions and can identify patterns that represent a typical fraudulent transaction – similar to the way spam emails are detected and deterred. Machine learning will start to affect other parts of your business funnel as well, just take a look at the rise of Chatbots.

Integrating Chatbots

There was a time in which chatbots were only thought of as manmade pests on the Internet, but through machine learning, they are getting smarter and businesses are embracing them en mass.

In 2018 and beyond, chatbots will play a key role in the future of customer service. Why? Chatbots can help achieve a faster customer service resolution, as well as provide quick histories of each customer for impeccable customer service. There are some key benefits that chatbots have over solely human interactions:
- Giving 24/7 customer service: The great things about machines? They don’t sleep! Coupled with the fact that chatbots are getting sophisticated enough to recognize human emotions such as anger, confusion, fear and joy. So should a chatbot encounter negative sentiments from the customer, they can seamlessly transfer to a human to take over and finish assisting the customer.
- The era of being ‘on hold’ is gone: A huge barrier to providing excellence in customer service is long wait times. How many times have you tried to get customer service from Comcast (or any TV/Internet provider) and you are getting progressively more frustrated with the wait times? This can all be eliminated with chatbots!
- Quick access to customer data makes service more personal: One thing that humans will never be better at than chatbots is quickly digesting customer data and history to provide context to customer questions. Chatbots excel at collecting customer data from support interactions. They can serve as virtual assistants that can feed customer data to your customer service officers so they have a full history of each account quickly.
This emerging tool for businesses already has significant buy-in from thought leaders around the globe. In fact, Larry Kim, Founder of Wordstream, is all in on chatbots as he has started his own company where his bots are currently in beta. With this move, it will be interesting to see how businesses will leverage robots throughout other aspects of their business. The final trend we’ll explore is Automation and how it affects businesses today.

Automation now and beyond 2018

Though Machine Learning and AI are hot topics in the tech world, it is not to a point that small to medium size businesses can leverage it in the immediate future. But there is still hope for them with automation. Powered by the Cloud, this type of technology has already revolutionized Marketing and Sales workflows and interactions but it is also starting to touch the various other parts of a business. For example:

Operations Automation

Once you win an important sale, you’ve got to deliver the product or service you’ve promised to the client. What does that process look like for most businesses now? You all will have a kick-off meeting and hope to cover all the promises that marketing and sales have given to your client.

However, with the use of operations automation and a powerful CRM, you will be able to read the interactions and see all the various touch points a client had with your company before that kick off call even happens. This will give all service businesses a head start in providing great client relations and managing expectations. This category of SaaS products is called Service Operations Automation, or ServOps for short.

Accounting Automation

If there is one data-entry heavy department it would be Accounting. The problem is that as humans, we are fallible and much slower at data entry than a machine. Innovations with bank feeds, rules-based categorization and integrated payments have dramatically reduced the workload of clerical and bookkeeping staff and given business owners more timely access to accurate financial information for their businesses.

Research, done by Xero, (a popular financial software provider) suggests that by 2020, automation will be commonplace in accounting, and a significant number of finance professionals will be using the next level of analytical tools to help them add value to business models across the globe.

Payroll/HR Automation

Finally, the Cloud and Automation have come to the Payroll and Human Resources sector. These important areas of a business too often suffer because small businesses aren’t big enough to afford a full-time HR department. What’s the alternative? Having only part-time efforts of founders and principals which can often lead to serious risk to the business.

For instance, Zenefits will automatically submit forms to the national tax authorities on the behalf of companies. With new automation technology, compliance is automated by platforms and the effort of keeping time-off approvals in sync with PTO balances and payslips becomes a thing of the past.

In the near future, we will see the rise of great technology, powered by the Cloud, Automation, AI and Machine Learning. This truly is the start of the Golden Age of Information Technology and it is time for businesses to take a hard look at their organizations and find ways to start integrating these tech trends.

This is a slightly shortened re-blog from a marketing post on Tenfold.com *

*This post was guest-authored by Tara Callinan and Jenneva Vargas from Accelo
23 July 2018
Cloud (Storage) Wars!

The term “storage wars” has taken on a new meaning. It has shifted literally from the ability to keep one’s belongings in physical containers to having one’s data stored and managed in the digital realm.

A question often asked is whether the (Internet) cloud is infinite. The answer is both a yes and no.

The top four cloud tech companies are endlessly engaged in a silent market share war. It is a tough choice as they all offer millions of gigabytes in storage. We can only attempt to investigate to what extent is there an abundance of storage when we ‘run out’.

The “Cloud” as explained in our previous blog, is a series of backed-up servers scattered across the globe.

Consequently, in terms of availability of storage, it is just a matter of where (location) a datacenter can be run and at what its maintenance costs are.
The answer to how infinite is the cloud, therefore, boils down literally to a cost, rather than a capacity issue for cloud-storage providers (CSPs).

The main CSPs vying for a market share in the paid cloud storage subscriptions are Google, Microsoft (Azure), Amazon, and IBM.

There are also smaller yet significant players such as Box, Dropbox, Tresorit, and Barracuda. A quick online search on their websites will reveal what they can offer you.

Similarly, the pages of any one of the smaller companies will give some comparisons of each cloud storage offer (bundles).

We will, however, focus on the major ‘players’ and summarize their offerings based on offers for both individuals and small to large enterprises.

What to look out for

Some of the key features to look for when storing data in the cloud include Encryption at rest and in transit, as well as end-to-end encryption; 2-Step Verification, HIPAA Compliance.

Other factors to consider are the actual server location, ability to sync any folders, and perform selective Synchronization.

There are also key offerings such as offering the ability to edit files on mobile devices. For businesses, the ability to remotely wipe mobile devices, perform file-versioning, and other useful features for data management.

As a business, if the above-mentioned features are not in your cloud solution, you better look into switching away.

While you can technically run your own cloud, it would require a full-on IT team. That or a very good support system to assist in its maintenance and administration.

It is for this very reason that a SaaS(and Hybrid)-approach to storage is preferred by many medium to large enterprises.

4 of the most popular CSPs

Google

Weaponry:

A standard (personal) GoogleDrive starts from 15 GB in size and comes when you open a Google email account. This is a standard with most Android-powered mobile phones which require a Gmail account to register the phone.

It is a convenient way to store and access your pics, videos, and files across multiple devices or back them up in case of a hard drive crash.
If you do not mind the inconvenience of having several logins, you could get away with multiple drives giving you 15 GBs each.

There is, however, a drawback as there is no such a thing as a free lunch – the level of security and compliance features naturally are little to almost none. Additional storage can also be purchased with different upgrade plans, which may come with more add=ons such as extra file encryption.

When it comes to their business offering, their Team Drive is available with the G-Suite bundle. One can upload 750 GB of data per day and up to a total of 5 TB in size. Team Drive can contain a maximum of 100,000 files and folders, however, this limit can be increased upon request.

The basic package including the more advanced security costs $5 per user per month and gives you 30 GB for storage and collaboration.

A full comparison of available storage plans

Tactical strengths:

The ease of accessing and using the drives via strategic partnerships such as Android provides them with a growing market share. As it is cloud-based and not linked to physical devices, you can access your GoogleDrive using a Mac computer as well.

There are growing talks of incorporating Artificial Intelligence <AI> into the data management systems. They are currently building a full AI Center in Accra, Ghana. This will help bigger companies manage, access, and organize their stored information faster and with more purpose.

They have recently launched a set of new cloud storage tiers under the branding Google One. This comes with revised pricing and storage options: 15 GB: remains Free; 100 GB costs $1.99/month; 200 GB $2.99/month and 2 TB $9.99/month.

Potential weakness/es:

Google is a latecomer when it comes to offering business solutions and still battles with the stigma of being a free service and thus associated with inferior quality.

The integration with Office applications is still something they struggle to get right. Not many are fans of Googlesheets.

Most non-Microsoft platforms will have this compatibility problem.
They also run into a few data syncing problems ever so often, especially with the free storage. Google offers full 24/7 customer and technical support with their products. More aggressive advertising and pricing of their business offerings now serves to hopefully alleviate this issue for them.

How Google bounces back from a hefty EUR 4,34 billion fine for colluding with Android will determine if they survive the storage war. This especially if they will be now forced to allow other CSPs to offer services on mobile devices.

Amazon

Weaponry:

One of the first cloud solution providers to offer eCommerce and Business-to-Business (B2B) offerings. Amazon and its Amazon Web Services (AWS) have come a long and calculated way from just offering/selling books online.

They are actually seen as a formal threat and a direct (more superior) competitor to Microsoft’s cloud (equivalent) offering – which we touch on next.
Most of this comes from a robust and apparently the world’s largest global cloud infrastructure.

Based on this, its cloud storage, dubbed Amazon S3, works on a “pay as you use” basis while its free tier starts you off on 5GB of storage. Thereafter you pay in increments based on the storage class you fall under.

So the first 50 TB will cost $0.023 per GB per month and then the next 450 TB will cost $0.022 per GB per month and so on.
This is practical for businesses that do not have a limit to storage space but scale up and down very quickly based on their operations.

Tactical strengths:

Amazon’s storage platform gives users and businesses alike the ability to geographically store and move data with the highest levels of encryption. In addition, one can use data analytics on your data without moving the data into a separate analytics system.

Amazon Athena additionally provides anyone who knows SQL on-demand query access to vast amounts of unstructured data. As with Google, AI incorporation along with Alexa would facilitate this even further.

Other notable benefits offered include open workflows, Hybrid-cloud storage capability, powerful APIs, and easy and reliable access to many Third-Party vendors & Partners.

Naturally, you get access to its AWS Marketplaces. It also has a strong compliance adherence including HIPAA/HITECH, EU Data Protection Directive, and FISMA.

Comparison of the various storage classes available.

Potential weakness/es:

Its primary offering of consumer goods and online delivery will make it prone to any bad press received if that arm of operations does not work well.

Further expansion into areas like streaming TV via Amazon Prime and cashless stores might result in a jack of all trades expert in none phenomenon. They are, nevertheless, handling all well so far.

Microsoft

Weaponry:

The “go-to” tech company for word-processing software as well as operating systems. This software giant like Amazon is branching into many products.

They now offer games, server hosting software, applications, an online store for all its devices, software, services, and of course, storage.
Its Azure platform powers certain parts of Nasa and utility giant Schneider Electric to mention a few clients. Its purchase works similarly to Amazon via ‘pay-as-you-use’ terms.

Storage users need to have a .Net Framework and SQL installed to use the storage. For those looking for quick storing solutions without building heavy infrastructure, they can adopt the cloud completely.

With the launch of its online services (Microsoft 365), it has had to repackage a portion of its Azure platform to cater to small to mid-sized businesses.

These include functional/specific bundles such as OneDrive (personal), OneDrive for Business, and Sharepoint (powerful storage and content management tool).

The online version of the Sharepoint starts at $5.00 per user per month for a rather limited 1 TB per organization. Thereafter, users can purchase more in 1 GB increments of 12 to 16 (US) cents depending on the total (storage space) size ordered.

Tactical strengths:

Also early adopters of AI (Machine Learning) and recently, the Blockchain (Blockchain Workbench), Microsoft is providing its developers with more and better reasons to use its storage space for practicality.
Like their online storage offers on Office 365, Azure storage packages are also quite structured and well categorised.

There are specific functions such as a database server-data management system. Then there is one for application running services, and others to handle rest-based object storage (Blob Storage).
Lastly, they offer storage to help perform computations and process events (Functions).
These bundles are all provided free for the first 12 months and then range from $0.002 per GB to about US 0.20c per million executions.

They have a good Partner system to help distinguish and provide support for the best storage package based on one’s immediate needs.

To bolster their growing Marketplace, they recently also purchased a business that deals with OpenSource (GitHub). This enables more freedom for developers to manipulate the software on their platform.

For a comparison of the storage types via Azure and pricing for each, click here.

Potential weakness/es:

People have found its pricing a little to steep on the storage side and so keeping market share will be tough. Many new smaller CSPs offering cheaper per GB rates.

They can only counter this by offering more products that require their storage (compatibility-wise).
Some other cumbersome restrictions like users being only able to upload 20 000 files at once or the actual file-size limit might not bode too well with heavy cloud data users.

They also don’t have as many APIs as Google or Amazon does, but these are growing by the day.

IBM

Weaponry:

Probably the first of the CSP batch that provided cloud computing. It therefore has had the experience of honing ways of storing and retrieving data for larger businesses. International Business Machines (or IBM) can be considered as the grandfather of data storage.

As with the other CSPs, there is a free offering called the “Lite plan” consisting of a single IBM Cloud service instance with storage up to 25 GB/month.
Paid storage is staggered, per consumption and based on complex costing tiers based on location, storage class, and resiliency choice.

Storage charges start from $0.09 for up to 50 GB down to $0.014 for 500+ TB on what they call the Cross-Region Flex plan.

For more insight into the complex costing table, visit the IBM storage pricing page here.

Tactical strengths:

Their security is their biggest pride and strength and makes them a firm favourite for large companies and potentially governmental institutions.
The fact that they do not actively advertise as much as Google or Microsoft is telling. They clearly need to provide high secrecy and protection for their existing clients.

One such feature unique to the way data is stored on their cloud servers is using Information Dispersal Algorithms (IDAs). This helps to separate data in unrecognizable “slices” that are distributed across datacenters.

So basically the complete copy of the data resides in any single storage node, and only a subset of nodes are available in order to fully retrieve the data on the network. This is similar to how peer-to-peer sharing or data encryption works.

And speaking of heavy encryption, they have allegedly recently also started on the Blockchain and are experimenting with a particular Cryptocurrency to enable ease of payments. This in the light of IBM with its Watson platform looking to become more of a cloud-based data operating system.

Potential weakness/es:

IBM relies too much on its reputation as a forerunner for tech and cloud-based computing. It has earned that title for several decades before the likes of Google and Amazon barged in.

They might lose out on market share once the newer CSPs start to offer more robust products and compliance services like theirs.

Their high security and complex system come at a premium so designed for or rather restricted to wealthy companies essentially. The hosting option (main server locations) looks limited and restricted to geographical areas primarily in the US and EU.

Be wary of clandestine terminology such as ‘unlimited archiving/storage’ even with a paid subscription. This usually refers to storing data at rest and not the ability to constantly and unlimitedly sync files.

Another salient factor to compare would be the number of files that you can upload or sync at the same time.
This will be relevant for larger companies that need to upload large files and by large, we mean 10 GB files (2 and a half HD DVDs’ worth of content) and upwards.

Making a choice

At the end of the day, your decision to take on a faction in the storage war should be based on your priorities. You simply match it to what each of the companies is offering taking your budget into consideration of course.

You may need to consider running a combination of two or more of them.
Some larger companies offer storage as a “must-have” with hosted email or something as basic as purchasing a new smartphone.

You will, however, have to ask yourself a few more pressing questions around functionality, data security, and compliance before taking it up.

Or you can simply not accept the offer or disable it in cases where it is presented as a freebie!

18 July 2018

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