Exploring Data Science with Microsoft Tools and Frameworks

data science

1. Data Science and its growing importance

An interdisciplinary field, data science deals with processes and systems, that are used to extract knowledge or insights from large amounts of data.  It uses a lot of theories and techniques that are a part of other fields like information science, mathematics, statistics, chemometric and computer science.

Over the last decade there’s been a massive explosion in both the data generated and retained by companies, as well as you and me.  Ninety percent of the data in the world today has been created in the last two years alone. Our current output of data is roughly 2.5 quintillion bytes a day.(Infographic 2017). Entirely different ecosystem is on the way to process, analyze such a huge data.  The Bigdata is a ultimate result of parallel processing of such a huge data in less time.

The Data Science is not restricted to big data, as big data solutions are more focused on organizing and pre-processing the data rather than analyzing the data.

Few of the analyzing methods which are core part of the data science are probability models, machine learning, signal processing, data mining, statistical learning, database, data engineering, visualization, pattern recognition and learning, uncertainty modeling, computer programming among others.  Each of them is gaining an importance at the enterprise level.

2. How data science may add a value to the business?

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3. Few trending Data Science platforms

The fastest growing importance of the subject in almost every business is leading to availability of wide spectrum of competitive tools in the market.  Different cloud technologies like Azure, AWS, Google, TERADATA are leading the bandwagon and providing highly user friendly services.

The Microsoft Azure provides ultimate range of products and tools to facilitate End to End unified development of analytical solutions. I am limiting this blog to discuss the range of solutions in Azure and their significances on the canvas of analytical technologies.

4. Data Science support in Azure

Having said that, lots of elegant special tools and solutions of workload of Data Science/Machine Learning have been introduced in the form of Libraries, Frameworks, Language API for development and production level deployment to meet the need.

(A) Analytical Language interfaces and tools:

The prominent languages data scientist and analyst use are Python and R (Java and Scala are also being used). In the interactive environment, this code runs interactively, with the data scientists using it to query and explore the data, generating visualizations and statistics to help determine the relationships with it. The commonly used tools include…

  1. The Jupyter Notebook and ‘Azure Jupyter Notebook’ as an online Jupyter service for data scientist to create, run, and share Jupyter Notebook script in cloud-based libraries.
  2. Spyder: An IDE provided by Anaconda Python Distribution.
  3. R Studio: An IDE for R Programming Language
  4. Visual Studio Code: A lightweight, cross-platform coding environment that supports Python as well as commonly used frameworks for machine learning and AI development.

(B) Data Science virtual machine (DSVM)

It is an Azure virtual machine image that includes the tools and frameworks commonly used by data scientists, including R, Python, Jupyter Notebooks, Visual Studio Code, and libraries for machine learning modeling such as the Microsoft Cognitive Toolkit, PySpark, MatPlotLib etc.  It can be used to create an environment ready container without needing to deal with complexities of installation, managing inter-dependencies of other tools w.r.t versions of different libraries and tools related to Analytics, Data Science, Machine Learning, Deep Learning, cognitive services and Neural networks.  Just few of the advantages are…

  1. The latest versions of all commonly used tools and frameworks are included.
  2. Virtual machine options include highly scalable images with GPU capabilities for intensive data modeling.

(C) Azure Machine Learning Services:

It is a cloud-based service for managing machine learning experiments and models. It includes an experimentation service that tracks data preparation and modeling training scripts, maintaining a history of all executions so you can compare model performance across iterations to choose one among best performing models.  The Azure Machine Learning Model Management service then enables you to track and manage model deployments in the cloud, on edge devices, or across the enterprise.

  1. The Azure Machine Learning WorkBench: A cross-platform client tool provides a central interface for script management and history, while still enabling data scientists to create scripts in their tool of choice, such as Jupyter Notebooks or Visual Studio Code. The workbench follows discipline of Team Data Science Process and provides solutions to follow life cycle from the point of Data Transformation up to deploying most performing Analytical or Machine Learning model for production.  It provides variety of ways of script execution environment like: run model training scripts locally, in a scalable Docker container, or in Spark.  When you are ready to deploy your model, use the Workbench environment to package the model and deploy it as a web service to a Docker container, Spark on Azure HDinsight, Microsoft Machine Learning Server, or SQL Server. The Azure Machine Learning Model Management service then enables you to track and manage model deployments in the cloud, on edge devices, or across the enterprise.
  2. The Azure Machine Learning Studio: It is a cloud-based, visual development environment for creating data experiments, training machine learning models, and publishing them as web services in Azure. Its visual drag-and-drop interface lets data scientists and power users create machine learning solutions quickly. It is enriched with a wide range of established statistical algorithms and techniques for machine learning modeling tasks and a built-in support for Jupyter Notebooks. It can do direct deployment of the trained models to the Azure Web Services. It’s a boon for data scientist who wants a quick solution without engaging themselves into to cycle of code development.
  3. Azure Batch AI: It enables you to run your machine learning experiments in parallel and perform model training at scale across a cluster of virtual machines with GPUs. Batch AI enables you to scale out deep learning jobs across clustered GPUs, using frameworks such as Cognitive Toolkit, Caffe, Chainer and TensorFlow. Azure Machine Learning Model Management can be used to take models from Batch AI training to deploy, manage, and monitor them.

(D) Tools for deploying Machine Learning Models:

After a data scientist has created a machine learning model, you will typically need to deploy and consume it from applications or in other data flows. There are numerous potential deployment targets for machine learning models.

  1. The Apache Spark on HDInsight: Apache Spark is a distributed platform that offers high scalability for high-volume machine learning processes. It allows Batch as well as Real time processing in the distributed manner. Well equipped with different kinds of analytical and ML libraries it includes Spark MLlib, a framework and library for machine learning models. Also its Microsoft Machine Learning library for Spark (MMLSpark) provides deep learning algorithm support for predictive models in Spark. You can deploy models directly to Spark in HDinsight from Azure Machine Learning Workbench, and manage them using the Azure Machine Learning Model Management service. The HDInsight instance of Spark can consume data from variety of Data Sources like Hadoop HBase, Hive, Azure Storage, Azure Data Lake, Azure Even Hub and last but not least Apache Kafka.
  2. Web Services in Container: Containers are a lightweight and generally cost effective way to package and deploy services. The Machine Learning Models are deployable on variety of platforms other than Azure Model Management. Deploy them as Python web service in a Docker container or to an edge device, where it can be used locally with the data on which it operates.  The ability to deploy to an edge device enables you to move your predictive logic closer to the data.
  3. Microsoft R Servers/Microsoft Machine Learning Server: It is a highly scalable platform for R and Python code, specifically designed for machine learning scenarios. The models designed in Azure Work Bench also are deployable to these servers.  The server instances can be created on-premise so is the good solution in case to abide by the business or company policies.
  4. Microsoft SQL Server: It supports R and Python natively, enabling you to encapsulate machine learning models built in these languages as Transact-SQL functions in a database. Thus it facilitates encapsulating predictive logic in a database function, making it easy to include in data-tier logic.
  5. Azure Machine Learning Web Services: The machine learning model created using Azure Machine Learning Studio, can be deployed as a web service which thus can be presented to consume through a REST interface from any client applications capable of communicating by HTTP. It also has a Built-in support for calling Azure Machine Learning web services from Azure Data Lake Analytics, Azure Data Factory, and Azure Stream Analytics.

(E) Visualization services:

Microsoft’s Power BI content pack for Microsoft Azure Enterprise Users is providing solutions at par with Tablue(BI and Data visualization tool) or Spotfire(Enterprise grade analytical platform). It is a suite of business analytics tools that allows you to explore to deliver insight and create visually compelling reports. It can connect to hundreds of data sources, simplify data prep, and drive ad hoc analysis. Produce beautiful reports, publish them for your organization to consume on the web and across mobile devices. Everyone can create personalized dashboards with a unique, 360-degree view of their business. And scale across the enterprise, with governance and security built-in.

5. Conclusion

The analytics and ML is one of the topmost trends today and certainly in coming years. Microsoft is striving to provide end to end efficient, highly scalable, reliable solutions for complete Data Science cycle from the phase of procuring, cleansing, wrangling, transforming data, applying different kinds of analytics and machine learning effects to the data, publishing the data model for the production up to visualizing static or real time analytical reports.  Their solutions are enriched with latest trends like Deep Learning, Neural analytics and Cognitive services for Predictive and prescriptive analytics.  All these solutions are not only cost effective but also are available as PaaS and SaaS services on their Azure Cloud making additional advantages.  Will take an opportunity to discuss more on Spark with Kafka and Azure Workbench in my next coming blogs.

References:

How to choose the best channel for your chatbot

socialChatbot

The chatbot is becoming a common fixture for companies online. The big question for them is which channel should they install it on?

The oft-repeated mantra you might hear from a real estate agent if you are buying a house. Forget the number of bedrooms, the size of the garden or if the windows are double glazed; it is all about which plot of land the house is situated on. What is true for your home is also true for the best chatbots.

The quality of your knowledge base is crucial. But a close second in importance is the channel you choose for your chatbot. Pick the wrong one and you risk alienating customers who are expecting certain functions from their virtual assistant based on the social media account or website they are using.

Within the last couple of years, chatbots have entered the mainstream and are employed in numerous channels – each with their own advantages.

Facebook Messenger chatbot:

Facebook boasts arguably the most populated social media channel for chatbots with more than 100,000 available to talk to its 1.2 billion users.

After it emerged that its bots were hitting a failure rate of around 70%, a recent update suggests a move towards concentrating on transactions and performing services rather than sparkling conversation.

Facebook bots will be a part of group chats to perform functions such as providing statistics around a sports match or creating a music playlist. Given it will be part of a group chat, the expectation around its conversational features will be low as it is simply performing an almost secretarial service.

In addition, functions such as Smart Replies will allow you to perform actions like viewing business hours or booking a restaurant table without leaving the chat window. These features all point toward Facebook bots designed to serve rather than interact with the customer.

Twitter:

Twitter appears to be trying a different approach with their bots, aiming to provide a medium for companies to interact with their customers to offer an experience which is fun, rather than transactional.

For example, the company’s Direct Message Card aims to draw consumers into testing out their chatbots by playing games or taking part in trivia. One example is the Bot-Tender which asks you a series of questions to help select your favorite cocktail, giving you the option to post the results later.

Skype:

On the same path as Facebook, Skype’s bots are generally utilized in group chats for functional purposes. One example can be found with the Skyscanner bot which can be called into a conversation if one member wants to book some flights.

One new addition will be the introduction of voice chat to provide users with an alternative to typing by accessing the Skype calling API. With this in mind, it is possible that their chatbots could become more interactive rather than strictly functional.

Slack:

While other channels are targeting themselves at the general public, chatbots on Slack are used internally by businesses to increase productivity, improve communications or manage tasks.

These bots can be divided into two categories: push and pull chatbots. Push bots aim to send you notifications or provide you with the information you need – be it reminders or important news of the day. These will generally be intelligent bots which rely on a foundation of natural language processing (NLP), artificial intelligence (AI) and machine learning.

Pull bots are far simpler and perform specific transactions which you initiate yourself. An example of this is the Uber bot for ordering transport.

Website:

Of course, one potential concern with the other channels is that you are not in control of your platform.

Within your website, you are able to dictate exactly how your chatbot functions, including its purpose, the user interface, and experience.

Implementing your chatbot on your own website, of course, means that the customer can engage in conversation without leaving the page. This is valuable for those looking to boost conversion rates and provide an easy way for customers to ask questions.

The chatbot window of opportunity is wide open for companies that want to transform their business. To get through this window, the onus is on businesses to recognize what channel will best serve their needs.

Inbenta utilizes its patented natural language processing and +11 years of research & development to create interactive chatbots with an industry leading +90% self-service rate.

Companies around the world including Ticketmaster UK utilize the InbentaBot to maintain a personal service for their customers while reducing support tickets.

Source: https://www.inbenta.com/en/blog/chatbot-choose-best-channel-chatbot/

How AI Makes Our Life Easy Through Chatbots

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Why chatbots at virtual service desk?

In today’s fast-paced life, no one has the patience to hold on to a customer service call for several minutes. No one likes hearing, “Your call is important; please stay on the line” or “all our executives are busy at the moment; please wait”.

Convenience is a key component of customer experience (CX) and even a single case of negative customer service experience drives away a potential and valuable customer from a company. To overcome this, one of the fastest growing companies in the world is coming up with chatbots to serve at their service desk.

According to Mark Zuckerberg, CEO of Facebook, “Messaging business has to be like messaging a friend.” It is also said that the best CX chatbot is one in which that the customer cannot identify as a human or a computer. This can be achieved by passing the Turing Test.

What is AI’s role in a chatbot?

The AI aspect in a chatbot is based on machine learning. It is known as Natural Language Processing; it has the proficiency to understand a conversation and mimic human speech. An artificial intelligence (AI) agent in a chatbot achieves the goal through the ‘sense-think-act’ cycle. In this cycle, the information we type/speak is sent to the agent and the information is then converted to machine language. It further continues to mine relevant data from stored information of the knowledge base and updates the newly gained knowledge to make a decision.

The final step is decision-making and during this process, the more intelligent chatbot prepares a few steps ahead for an expected series of questions and then modifies its decision per need. Later, the decision is turned into an action in form of text or voice chat.

How to measure the intelligence of a chatbot?

The intelligence of a chatbot is evaluated on the basis of NLP and its understanding of information even when you construct it in an incorrect way. The other important intelligent factor of a chatbot is the memory; it should be able to remember who you are and respond accordingly. Just remembering is not enough; it should learn the pattern of your choices, issues, likes, and routine. For example, in online retail portals, chatbots must remember and recall your preferences of color, size, brand, etc.

However, AI and conversational skills should go hand in hand for a successful chatbot. The conversation has to be more interpersonal. Language crafting and conversation scripting skills are considered the heart of a chatbot’s UX design.

What are the current challenges with chatbots?

Chatbots can help in solving various customer problems, but sometimes, the problem itself arises from a chatbot. One of the major problems in a chatbot is that it cannot think contextually.

Chatbot

Chatbot being unable to understand the context when asked for the menu

AI has made life so easy that it also has its disadvantages; it memorizes all your personal and bank details when you place an order online with the help of a chatbot.

Imagine telling Google assistant, “Ok Google, order me a backpack” and it proceeds to order with your existing bank information. But this can be done even by a friend or a stranger who has your mobile phone. An authentication (like voice/fingerprint/signature) process has to be factored in before proceeding with any of the bank transactions to avoid cases of fraudulence. These problems will be addressed very soon with further development of AI.

What is the future of chatbots?

Eventually, the goal of a futuristic chatbot is to be able to interact with users as a human does. As the saying goes, “the best interface is no interface.” Voice chat is trending with the introduction of smart speakers like Amazon Echo, Google Home, Apple Homepod, etc.

The shift is happening from NLP to NLU, and so the focus is on allowing machines to have a better understanding of the user messages. The advantages of using a CI is to increase the user attention by providing the information progressively based on the user’s previous inputs as an option.

Source: https://www.hcltech.com/blogs/how-ai-makes-our-life-easy-through-chatbots

How Chatbots Can Pair with Email to Achieve Your Marketing Goals

In today’s fast-growing technology world, you must be up to date with latest emerging technologies. You must be ready to survive in the market with your uniqueness. It’s very important how you can attract the customer? The answer is “BOT”. To attract the customer using BOT technology is a very great way.

Let’s see, What Exactly BOTs are?

Basically, BOT is an Artificial Intelligence. It is a computer program which is able to talk or chat with customers. BOTs operate as a virtual assistant for customers or other programs and its behavior is like human beings. They also are known as Chatbots, Spiders, and Crawlers. They are having the ability to understand questions, order etc. and for that, they give appropriate response and answers. They access Web sites and gather their content for search engine indexes.

Advances in artificial intelligence are changing the ways businesses are able to communicate with their audiences and it is proving to be very effective. As a result, chatbots are becoming one of the best ways to engage customers.

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Recently, we have seen a lot of articles that discuss chatbot marketing vs. email marketing. Since chatbots are receiving high engagement rates while the open and click-through rates of email are declining, it is not a surprising conclusion that chatbots are more effective than email marketing.

Many companies are lucky to get a 5-10% open rate through email marketing, while Messenger chatbot marketing through Facebook Messenger boasts an average 70-80% open rate in the first hour. Not a lot to argue with there in terms of chatbot marketing vs. email marketing, but you also need to consider that email marketing still delivers great conversions.

Why Email Marketing and Chatbots Complement Each Other

You would never use just one marketing channel, so there is no reason to abandon your email marketing tactics just because Messenger chatbot marketing is performing better. By creating a strategy that joins email marketing and chatbots, you can get the results you crave.

These two channels can very often have different functions. An email drip campaign can be great for telling the story of your brand, while a chatbot can be used best for answering customer service questions in a timely fashion. It is important to understand which platform – chatbot marketing vs. email marketing – is best for certain use-cases and act accordingly.

It is also possible to promote one channel on the other and get even higher engagement on both. For example, use your email marketing to inform your customers of your customer service chatbot.

You can also use your Messenger chatbot marketing to gather email addresses. Then, offer subscribers content through your bot and ask if they would like to receive similar media via your newsletter. This kind of cross-promotion is a great strategy for integrating email marketing and chatbots and in turn gain more users on both channels.

Furthermore, statistics show that 33% of 18 – 24-year-olds prefer to buy products directly from Facebook. Since you are able to allow customers to purchase your products directly from your bot, the use of Facebook Messenger chatbot marketing may be the ideal situation. If you’re also running Facebook ads, you will see even more reach and success. Support this with an email marketing strategy, and the sky’s the limit!

Source: https://snaps.io/chatbots-can-pair-email-achieve-marketing-goals/

Modern Learning: Grow Your Cloud Muscle with New Azure Training

by Eduardo Kassner on 11 January 2017
Chief Technology Officer, Worldwide Partner Group

The future of cloud is here — and we want to help you prepare. A recent IDC study reported that within IT organizations, certified staff members earned 15% more on average than staff without certification. Skilled Azure professionals are highly sought after in the job market. Technical certification gives you opportunities for career advancement, higher salaries, and more interesting work.

We know it can be difficult to master all the latest Azure skills in today’s increasingly complex technological environment. That’s why we’re always looking for ways to increase our offering of flexible, modern learning methods from Massively Open Online Courses (MOOCs) to certifications. Not sure which option is best for you? Here, we answer your top questions about modern learning.

What is a MOOC?

Massively Open Online Courses, or MOOCs, are self-paced, interactive online learning environments that focus on core development skills for cloud and mobile technologies. The individual MOOCs are from 4–18 hours in length and provide high-tech job skills training, giving you the chance to move forward with your own skill-building online. With a variety of videos, labs, graded assessments, office hours, and more, our MOOCs will allow you to learn, apply, and validate your skills.

What’s the difference between video learning, MOOCs, and exams?

To help provide the training you need, we have a flexible catalogue of learning methods with a comprehensive selection of MOOCs and certifications. Not all people want to learn by the same method, or you may want to go deeper on a topic in a different format. With our flexible learning methods, you can do just that.

modern learning graphic

Should an IT pro who wants to learn Azure take a MOOC or a certification exam?

We’ve built a flexible range of learning methods to help you get up to speed with Azure, including both MOOCs and certification exams. This way, you can choose to study as part of an online course with hands-on learning experiences as rigorous as a traditional classroom setting but set at your own pace, or take a specialized certification exam to prove your skills. After completing your certification exam, you’ll receive a digital badge ready to share on your professional networking sites. Additionally, as an IT pro, you have the flexibility to select which MOOC courses or exams to take based on your own needs and knowledge. We encourage you to choose the option that works best for you.

Boost your Azure skills today

Today, with almost 80% of business deploying cloud technology, cloud is the new normal. And with triple digit growth over each of the last eight consecutive quarters, customer demand for Azure is going up fast. Ready to start increasing your Azure skills? We’ve recently launched a variety of new Azure training courses, including:

  • Azure Fundamentals
  • Azure for AWS Experts
  • Azure Virtual Machines
  • Azure Networks
  • Azure Storage
  • Azure Identity
  • Managing Azure Workloads
  • Automating Azure Workloads
  • Azure App Service
  • Databases in Azure
  • Azure Security and Compliance

We’ll also be launching Azure App Services, Databases in Azure, Azure Security, and Application Deployment and Management later this year.

Overall, we’re offering opportunities for Azure certification at a deep discount. These offers are a high-value, simple, and customizable way to increase the technical skills of your team and earn valuable Microsoft Certified Professional designations to set your business apart.

New Cloud Console for Azure Portal

Cloud services are usually managed in two interfaces available. Traditionally, they are managed in either a web-based graphical interface or a command line terminal interface. Each of these interfaces provide their own utility. Different users prefer different interfaces for different tasks or whichever suits best for them. There are many Azure users who use both the interfaces in order to manage their applications on Azure. That’s where the problem arises. Switching between these interfaces requires switching between applications and a terminal, a context switch that slows users and makes it harder to accomplish their goals. Whereas, in some cases such as mobiles or tablets, a terminal interface itself may not be available, thus making the user switch devices.

According to the latest blog from the tech giant Microsoft, this software master has come up with a solution.

The new Microsoft Azure Cloud Console comes with an integrated workflow. It allows users to build their applications on Azure using graphical and command line tools, even on devices which does not have command line installed within them. The shell is integrated in the portal so that the users can quickly drop in a command line experience while simultaneously viewing their cloud resources in the graphical web interface.

The key features of this experience are:
■    Automatic authentication to the command line tools from your existing web login
■    All Azure command line tools, as well as relevant command line utilities pre-installed
■    Personalized, persistent workspace that preserves your code, configuration and activity across cloud shell sessions.

Brendan Burns–the Partner Architect at Microsoft writes in the blog–“The terminal is a fully featured experience featuring not only the Azure command line tools, but also standard editors and tools you would expect. Further, the cloud shell preserves context for you”.

Additionally, the users can continue where they left off in the next cloud session as the files gets saved to the disk are persisted in Azure’s cloud. It is not even necessary for the users to be on the same device and network in order to continue the session.

What are the advantages and disadvantages of Microsoft Office 365

Microsoft has made a rather significant shift in its new SharePoint platform. The new SharePoint Online which is available with Office 365, includes a variety of features. This step of Microsoft moving into the cloud with the new office 365/ SharePoint Online version is accepted by many with open arms, but still, there are IT Directors who are hesitant to move their important content to the cloud. As with all things that you hear around, some which sound too good to be true, there are possible compatibility issues which you must know before you make any decision for your business.

Your decision must be made keeping in mind the requirements of your business, the type of business you operate and the size of your company along with the needs of the end user. Microsoft Office 365 has various subscription levels with annual commitments for the small businesses, education, government organisations and enterprises. The product is cloud-based and offers a variety of options, however if your business has strict regulatory constraints regarding customer security, you will most likely need to ensure security levels and email archiving protocols.

With this blog post, we hope to highlight some of the advantages and disadvantages that you should consider when evaluating SharePoint Online.

ADVANTAGES

Cost effective

When it comes to paying for licenses, Office 365 is certainly the less expensive, depending on how many users your office requires. With the subscription model you have, you will automatically receive upgrades thus you don’t have to pay for any new software every time Microsoft issues a new release. Additionally, since you pay by the user, you are only paying for the resources you are using.

Storage Drive

Each user of yours will have access to One Drive which depends upon your service level offer up to 1 terabyte of storage, per user in a cloud environment.  You could share and sync files on a limited basis through some permission-based featured. If your users requires additional storage, you can easily purchase that too.

Easy access to files

Another great advantage is that the plans of Office 365 offers access to Word, Excel, PowerPoint and other programs through an online web version of the program. This will be immensely beneficial for those who travel or remotely work. Through this facility you can open and edit your documents from any device and browser. Mobile apps are also available for the same purpose, you can download and give it a try.

Email is accessible and affordable

You would be able to access your email anywhere, anytime since Office 365 Outlook is hosted in the cloud. Most of the Office email options don’t require any administrator or hosted exchange server, thus making it affordable for the smaller sized companies. Most plans are administered through a user-friendly interface that doesn’t require an IT professional at all. But if your business is vast and requires more robust controls, many of the enterprise versions have a PowerShell interface within them that administers permissions for email and other programs.

Scalability

Just as anything built in Cloud, Office 365 also allows your business to scale from one user to around 300 users. When your business will grow Office 365 will not disappoint you. It will scale up to meet your requirements.

Additional Tools

Skype, SharePoint and Lync Online are the extra features available in Office 365. They will be better for communication and collaboration across your business.

Business continuity

Built on Microsoft Azure platform, Office 365 offers a reliable infrastructure which is secure and reliable.

DISADVANTAGES

Cost considerations

There are often budget choices, i.e., Cap-Ex vs Op-Ex, or your business could be a seasonal one and the recurring fee may be caused due to the budget constraints. Thus, while the office 365 subscription is usually more cost-effective for many business, it many not work so well for your seasonal business.

Infrastructure configuration:

Since Office 365 is built in the cloud there is less flexibility and customization. If you have a hybrid set-up, (combination cloud and on-prem) you might need to have a third party involvement or add-ons when it comes to other collaboration tools or emails.

Data Security

Your information does not not reside, as with any cloud-based solution. Here it will sit on a Microsoft server. Many businesses find this as an secure option, but there are industries such as healthcare and financial services which are bound to comply the regulatory constraints and require data to be stored on-perm. Microsoft does offer options for these businesses as well, but they are more expensive and may not completely satisfy requirements.

Email Archiving and eDiscovery

When it comes to archiving and eDiscovery tools, Office 365 has limitations. If your business is regulated then you have to ensure that there are no restrictions in your plan in email retention and archiving. While Office 365 boasts an eDiscovery tool, it may not be necessarily part of your plan or easy to administer. Examine all these features before migrating to Office 365. To ensure compliance you might require an addition of third-party email archiving service provider.

Email quotas and limitations

There are limits placed on how many emails you can send and receive in one day, unlike on-prem exchange servers. All these vary with subscription and Microsoft is working to improve size and quota. Before moving to Office 365 your business must investigate this.

Today when the technology gets advanced everyday, weighing the advantages and disadvantages of any platform requires in-depth research which begins inside your business. There is no doubt that Microsoft Office 365 is helping many businesses in saving their money and capitalizing on the cloud; but you may need to thoroughly consider and investigate the limitations, and address any workarounds or the addition of third-party vendors if required.