How to Become a Data Scientist in 2020

How to Become a Data Scientist in 2020

Data Science has been one of the trending technologies for more than a decade now. The science of all data involves analysing millions of data units to find hidden information. The insights gained from the information help the stakeholders make informed decisions. With the increase in the demand for data, the demand for data science tools and applications has also increased. This domain has also spurred the development of other technologies such as artificial intelligence, machine learning, deep learning, IoT, robotics, and neural networks. With such a wide scope across all sectors and industries, there is always a huge demand for skilled Data Science professionals.

Advanced Data Science

Advanced data science course curriculum includes basic data analytics tools and techniques as well as advanced ML and DL tools and technologies. The advanced training program helps you specialise in niche ML concepts that will help you learn to create ML algorithms. In the training program, you will also learn all about neural networks and NLP.

Steps to Gain Data Science Expertise:

One of the chief challenges of data science aspirants is to bridge the gap between knowledge and application. In order to build a successful career in Data Science, aspirants should have the essential skills, portfolio, and certification.

Learn the skills

The mandatory skills required to become a data science professional are:

  • Knowledge of programming languages such as Python and R
  • Knowledge of databases, especially SQL
  • Ability to use Data Science tools and techniques
  • Knowledge of advanced mathematics, statistics, and probability
  • Machine Learning algorithms

If you come from a non-computer science background, then you can do basic training in Python programming before you take up the advanced data science program. Then, you can learn the other technical skills essential for a career in Data Science by enrolling in one of the Data Science certification programs from LearNow. There are different  courses where you will learn all about data science, from the basic to advanced levels. The training will equip you with the working knowledge of Excel, Hadoop, and other data analytics tools. You will also learn about deep learning and machine learning in the training.

There are many ways you will benefit by joining a Data Science course. The first benefit is that you will be trained by expert academicians and industry experts. Also, interactive training sessions will help you understand the core concepts of technology. You will earn an industry-recognised certification, which will enhance your prospects for building a career in this domain.

Build your portfolio

The second step to gaining expertise in data science is to build a portfolio. A certificate can get you inside the door. But a well-done portfolio can help you secure the job. It is because the project work showcases your learning and understanding better than answering a hundred questions at the interview. When you’ve done the project from the start to finish, you will be able to confidently answer all the relevant and related questions. The confidence in your subject knowledge will make you a winner.

Why Get Advanced Data Science Certification?

The first step to build a career in the field of Data Science is to earn an Advanced Data Science Certification from a reputed institute. The certificate will help you stand apart from the hundreds of others who have applied for the position. Also, the training program will equip you with the essential skills and working knowledge of data science tools and technologies. The in-depth training will make you job ready. The best thing about this domain is that anyone with the right skills and abilities can work irrespective of your background. Even if you are from a non-technical background, if you learn the basics of Python or R programming, you can join the Data Science course and start your career

There are numerous career opportunities for professionals in the field of data science. A few of the job profiles are

  • Data scientist
  • Data architect
  • Data analyst
  • Research analyst
  • Business analyst

Data Science tools and applications are now being used in various sectors including education, healthcare, research and development, infrastructure development, and even marketing. So, there is a huge scope for certified professionals in this domain.

Just as the demand for data science professionals is more, the competition is also equally high. A strategic job application will help improve your prospects of finding a good company in this field. First, you need to update your LinkedIn profile and follow the right companies to get updates. Second, make your profile “All-star” by building a contact list of at least 500 members. Follow niche-career boards. If the organisation is good and there are prospects for career development, accept the position. You can move further as you build your professional experience.

Earn an Advanced Data Science Certification from LearNow

The certification at LearNow will you bridge the gap between learning and practical application. To do this, we follow an intensive, regularly updated curriculum that is designed by industry experts. We also use interactive teaching methodologies in our training program. The online training sessions allow aspirants to learn at their own pace. We also organise live webinars with Q&A sessions that allow students to interact with the trainers. On completion of the training program, you will receive an industry recognized certificate, which can improve your career prospects.

Contact us to know more about our Data Science Certificate Programs.

Top 5 Data Science Trends of 2020

Top 5 Data Science Trends of 2020

The world revolves around Data! Companies need customer data to check if their products or services meet customer expectations. Pharma companies need data to find out if their new product has been successful or not. Educational institutes need data to evaluate the reach of their new training program. These are just a few examples of how data is being used across the sectors. In fact, we can say that data is the key enabler that organisations use to evaluate their performance and identify ways of improvement and expansion.

Data science is more about data and numbers. It is an umbrella technology that contains various other technologies such as artificial intelligence, machine learning, deep learning, neural networks, business analytics, and lots more. As technologies emerge, data science trends evolve. The top 5 data science trends of 2020 are:

1. Access to Artificial Intelligence and intelligent apps

Small and large companies have already started using AI-based applications. In 2020, we will see a rise in intelligent applications designed using ML, DL, and AI technologies. Automated machine learning will be used along with data science to enable efficient data management.

2. Rapid growth in the IoT

According to a survey conducted by IDC, the investment in IoT apps and solutions will be nearly $1 trillion by 2020. Until now, IoT was used in home automation, self-driving cars and automating manufacturing processes. However, this year, we can see more research and development in the applications of IoT in agriculture, city management, retail industry, and other sectors.

3. Evolution of Big data analytics

Businesses have found the huge benefits of Big Data analytics. This year will see more companies use data analytics to improve their profit margins. Predictive analysis will also become more popular. Businesses don’t just want to use data to understand what has happened, but also predict what could happen in the future.

4. Edge Computing will be on the rise

Edge computing is a process that analyses data in real time. The data is stored near the source itself so that it can be analysed just as it is being produced. The increasing applications of IoT have risen the demand for real-time data analysis. In IoT, sensors and devices collect data, which is immediately transferred to Cloud storage. Using edge computing, the data is immediately analysed and actions are taken. This synchronised structure speeds up the decision-making process and at the same time ensures it is accurate. It also allows applications to react immediately, which is one of the essential characteristics of an Internet of Things system.

5. Demand for Data Science Security Professionals

With huge volumes of data being used across various systems and applications, data vulnerability increases. Though there are numerous applications of data science, many are still sceptic of using it because of the security challenges. So, there will be a huge demand for data science security professionals this year. These professionals should be experts in the latest data science technologies and have in-depth knowledge of Python concepts. So, they can deal with data issues with confidence.

Benefits of Learning Data Science

Data is a vital component of any organisation. Data science is one of the fast-growing technologies that is finding applications across all horizontals and verticals. Organisations rely on data to make informed decisions. For example, customer data is used to evaluate the performance of an organisation and at the same time used to identify ways in which a product or service can be improved. Data captured from social media help organisations gauge people’s opinions about their company, services, or products. Data science applications are used not just in product-oriented organisations, but also in service-oriented organisations. So, you can see that the scope of job opportunities is enormous. Even if you are from a pure science background or medical background, you can learn data science and find better career opportunities in your field itself. Data science is the present and the future. So, you will have many opportunities for career growth once you complete data science certificate course.

Advanced Data Science Courses

The in-demand skills for a data scientist are knowledge of programming languages such as R, Python, and Java. Data scientists should also know about applied mathematics and statistics. They should have in-depth knowledge of databases, machine learning, deep learning, and working knowledge of the data science tools. Advanced data science courses should equip you with these skills and capabilities. The curriculum of the advanced data science course offered at LearNow includes

  • Introduction to machine learning
  • Linear regression
  • Data visualisation using python
  • Decision Trees
  • Logistics Regression
  • Clustering
  • Text Mining
  • NLP
  • Artificial Neural Networks
  • Convolutional Neural Networks
  • Recurrent and Recursive Networks

The advanced course will be suitable for a working professional who wants to upskill themselves and enhance their career prospects in this domain.

Career Opportunities in Advanced Data Science

Once you have earned a certification in advanced data science, you can apply for various job profiles such as

  • Data architect
  • Data scientist
  • Data statistician
  • Data analyst
  • Data engineer
  • Data administrator
  • Business intelligence manager
  • Data analytics manager

Join Advanced Data Science courses at LearNow

LearNow offers Data Science Certification Course for graduates and working professionals. This professional course is designed and delivered by experts who come with nearly a decade of industry experience. Aspirants can join the Executive program in Data Science or Advanced Data Science course based on their preference and eligibility criteria. The curriculum includes 4 to 6 industrial projects, which will give students a working knowledge of the concepts they learn in the training. LearNow offers online training sessions that are interactive with use cases, discussions, quizzes, and more. Students can join the live training sessions from anywhere in the world. In case, you miss a session, you can watch the recorded session or opt to join a live session being conducted for another batch.

Upskill yourself in the advanced concepts of Data Science by joining our online training program. Contact us for more details.

What is the Internet of Things (IoT) and How it works?

What is the Internet of Things (IoT) and How it works?

The Internet has made the whole world as one interconnected network. Social media platforms allow people from all parts of the globe communicate with each other. Job portals enabler recruiters to find talent in any part of the world. The internet has not just brought people into a network, but also machines. This technology is known as the Internet of Things.

1. What is IoT (Internet of Things)?

Internet of Things refers to the network of devices connected via the internet. It allows for real-time communication between machines without any human intervention. The earliest known reference to technology similar to what we now call IoT was discussions about using sensors to operate machines. They even tried to set up an internet-operated vending machine. But then the chips were large and technology was not so updated, so the concept was not successful. After many years, RFID technology was developed. This technology enabled wireless connectivity between chips. In 1999, Kevin Aston came up with the phrase “Internet of Things.” But then it took nearly 10 years for this concept to become a reality. As machine learning and artificial intelligence developed, IoT also started developing at a rapid pace. Now, many organisations and companies are adopting this technology as it has many benefits.

2. What are the benefits of the IoT?

Businesses can greatly benefit by using IoT. This technology can be used to create a seamless workflow in which repetitive tasks can be automated. In some cases, it can be integrated with data analytics. So, the ML-based application can use the data obtained by analytics to self-learn. Automating processes reduce process time and increase in quality. It also reduces the percentage of human errors.

Manufacturing Industries

Sensors can be integrated into the products when they are being manufactured. These sensors can transmit data regarding performance and other metrics. All this information can be used to enhance the quality of the product. At the same time, if the data indicates that any component of the product is likely to collapse or fail, it can be replaced at the earliest. These methods will enhance product quality and performance.

Supply Chain Management

Right data delivered at the right time is one of the most important factors for the success of a supply chain. IoT techniques and solutions can be used to build a network that connects warehouse, logistics, manufacturing unit, and destination company. The network will keep all the stakeholders informed regarding the location of the shipment via GPS. It enables efficient communication and coordination.

3. How IoT Works?

The four major components of an IoT network are sensors & devices, connectivity, data processing, and user interface.

Sensors/Devices

Sensors or devices collect data from the environment around them. Depending on the size and the complexity of the IoT network, it can have just a few or a few thousand sensors. A simple example is a Smartphone that we use every day. It has sensors such as GPS, camera, accelerometer, fingerprint sensor, facial recognition sensor, and such. All these sensors capture the relevant data and pass it on to the processor, which then analysis the data.

Connectivity

The medium used to transfer the data from the sensor to the data processing unit varies from one IoT network to another. The various mediums of connectivity are Bluetooth, Wi-Fi, LAN, WAN, satellite network, cellular network, and wired communication.

Data Processing

The third component refers to the software application that processes the data obtained from the sensors. The data processing depends on the algorithm and the goals of the IoT application.

User Interface

The user interface is where you get to see the results of the analysis. The user interface can be a dashboard, a text message, an alarm, a call or anything else that is used to give you the information.

4. Why Learn the Internet of Things?

Internet of Things is an emerging technology that is fast being adopted across various sectors. IoT applications are used in security, home management, agriculture, smart retail, smart grids, environmental protection, healthcare, and urban management, just to name a few. Skybell, Deako, Mymdband, Particle, and June are a few of the companies that are already producing IoT products. There are other large brands that are also exploring the applications of IoT and artificial intelligence. So, the future is in IoT. Learning the Internet of Things can help you build a career in this domain. Also, IoT professionals are the highest paid in the software domain. So, join IoT training online and upskill yourself and enhance your career prospects.

5. What are the Job Opportunities in Internet of Things?

There are numerous job opportunities available for freshers and working professionals in this domain. The top IoT careers are:

  • Professionals in sensors and actuators
  • Embedded programs engineer
  • Software engineers
  • AWS IoT engineer
  • IoT architect

6. What is the Salary Package of Internet of Things?

The salary depends on various parameters such as experience, certification, graduation, performance, and the city of work. The average salary for freshers in this domain is around Rs 3.5 to 6 lakhs per annum. Mid-level professionals can expect an annual salary package of around 10 to 25 lakhs. Professionals in senior level positions can earn up to one million per year.

7. Who Can Join the Internet of Things Course?

Engineering students who have basic knowledge of computers and the internet can join the Internet of Things course to improve their career prospects. Working professionals who can take up this training are electronics or IT engineers, embedded developers, Cloud solution architects, and network engineers.

8. How to Learn IoT Through LearNow?

LearNow is a reputed training institute based in Bangalore that offers IoT training online. We follow a project-based learning methodology that focuses more on practical applications rather than theoretical sessions. Aspirants who take up our Internet of Things course will need to work on mini projects and a big project. There are many benefits that you will gain by enrolling in our IoT course. First is that you will be trained by experts who come with industry experience. Also, you get to work on real-time projects, which will help you easily adapt to the work environment. Finally, we offer placement support. Based on your overall performance and project, we can help you start your career in a reputed organisation.

If you want to build your career in the domain of Internet of Things, you can join our IoT training online. Contact us for more details.

20 Real World IoT (Internet of things) Applications/Examples

20 Real World IoT (Internet of things) Applications/Examples

IoT or Internet of Things is a trending technology that has applications in many sectors, from security to farming. IoT can be defined as a network of devices that are interconnected with each other. The number of devices in an IoT network can be anywhere between 2 or 3 to hundreds. Sensor technology and automation are very important functions in IoT. In this blog, we will look into 20 real world Internet of Things examples.

Application 1: Connected Car

You would have read about cars that run by themselves in sci-fi books or watched them in movies. AI and IoT have made that dream a reality. Now, there are cars that can run by themselves. The self-run cars can work on voice commands transferred over a connected smartphone. They can also predict machine failure in the early stages or even before they happen. A smart car is capable of analysing obstacles and blocks and preventing accidents, but scientists are still not sure if smart cars can handle the traffic conditions on the road. Right now, connected cars are suitable for controlled environments.

Application 2: Smart Home

While talking about IoT applications, Smart Home is one of the first things that everyone talks about. A smart home IoT connects appliances used at homes such as washing machine, coffee maker, microwave oven, security system, air conditioner, and refrigerator, and even the lighting system and the door. You can control all the devices from your smartphone or computer system. The appliances can also be automated to start and stop at specific times. When you are going back home in the evening, you can activate the lights at home just as you get near to your house. You can also check if the door is locked or if the dishwasher is turned off right from the connected device. IoT Smart homes can help you save on electricity.

Application 3: Smart City

Smart City is a dream that can be made real with the help of IoT and artificial intelligence. This network can include water management, street lighting, electricity management, traffic management, waste management and more. By integrating sensors in buildings, we can detect wind pressure, seismic activities, and other natural factors to predetermine natural calamities.

Application 4: Precision Farming

Another of IoT’s applications is in precision farming. Data science tools can be used to collect and analyse data such as humidity, soil pH, weather conditions, rainwater availability, and lots more. The nutrients in the soil and its pH can be analysed to determine which plants will grow best. IoT can be used to remotely activate the water pump or turn it off while irrigating the fields. It can also be used to control the flow of water in drip irrigation. There are numerous other ways in which technology can be used to improve agricultural practises and enhance yields.

Application 5: Agricultural Drone

A drone can be used to survey large stretches of land to see if there are any problems such as rodent and pest attacks, evaluate the health of the crop and check if there is any water stagnation in the fields. Drones can also be used to spray fertilizers and weedicides in the field.

Application 6: Smart Grid

A Smart Electric Grid can be used to optimize electricity usage based on customer requirements. When the load is heavy, it can give recommendations to customers to reduce usage. In the case of electric failure, the electric grid can be programmed to reroute electricity.

Application 7: Connected Factories

A connected factory can be built using IoT. This technology can take over the job of a supervisor and still do more. The factory can be run round the clock with minimal human intervention as most of the tasks and transport are automated. The labourers can be asked to work on safe tasks while dangerous tasks can be handled by machines.

Application 8: Smart Retail

IoT can make shopping a more enjoyable experience for customers. There are many ways in which AI and ML can be applied in large retail outlets. Automated checkout counters reduce the need for long queues and allow customers to self-checkout their purchased items. The bill can be paid via digital payments. Sensors can be placed on the shelves, which will send notifications when the products are out of stock or if the stock has reduced. Automated inventory management makes it easy to manage product availability in the store.

Application 9: Supply Chain Management by IoT

Supply chain management is a complex process that involves many steps and human intervention in many areas. IoT can help streamline the supply chain management process, right from the procurement step to the delivery stage. Shipment tracking, inventory management, scheduling of product arrival and departure, and other processes involved in supply chain management can be automated and connected to ensure a seamless experience.

Application 10: Traffic Monitoring System by IoT

IoT can also be effectively used for traffic monitoring with minimal human intervention. The traffic signals across different roads can be connected and designed to change based on a specific algorithm. It will need human intervention only in cases when there is an ambulance movement or any other emergency. Surveillance cameras can be set up beside traffic signals or other parts of the road to monitor traffic. The videos captured can be studied to check for traffic violators or any other purpose.

Application 11: Forest Fire Detection by IoT

Remember the recent Amazon fire and that huge fire in Australia that destroyed millions of acres of forest cover, wildlife and even human life and property? In most cases, forest fires can be stopped if detected early. Different kinds of sensors such as temperature sensor, humidity sensor, soil moisture sensor, accelerometer sensor, ultrasonic sensor and others can be setup to track and identify minute changes in the environment. The data gathered by the sensors can be analysed to see if there are any indications for a forest fire. If so, precautions can be taken to prevent this natural calamity.

Application 12: Portable Water Quality Assurance

A survey shows that if the current rate of environmental pollution continues, then nearly one-third of the world population will not have access to good portable water. Sensors can be used to detect salinity, pH, turbidity, oxidation-reduction rate, and other parameters to determine the quality of water. The sensors can also be used to detect arsenic or lead poisoning at the early stages. IoT can be used to determine the quality of water in reservoirs to ensure that all residents get good quality water.

Application 13: Structural Health Monitoring

Structural health monitoring through IoT helps check the stability of construction at periodic intervals. Sensors can help collect data related to structure strain, vibrations, crack widths, moisture, and lots more. The data can be analysed to evaluate the remaining life of the structure.

Application 14: Radioactivity Monitoring

Nuclear power plants generate huge volumes of power. The downside is that there is always a chance for radioactive leaks, which can lead to very dangerous consequences. IoT applications can be used to continually monitor radioactive levels in the nuclear reactor and the surrounding regions. GM counters can be used to gauge the radioactive levels and send the data to the Cloud. A Node MCU and GPS can be used to detect the location from where the data was sent. All this information can be collated to identify risks at an early stage.

Application 15: IoT Controlled Golf Course

All IoT application examples are not just for environmental protection and individual safety. There are a few applications that are also used in sports, for example golf. There are many factors such as humidity, soil moisture levels, rainfall, and other conditions that determine the gameplay. Using sensors, all these factors can be monitored and updates sent to a connected device. The golf course can be neatly maintained based on this information. At the same time, this data can be shared with golfers, which will help them plan their game.

Application 16: IoT in Packaging Industry

Market studies determine that the packaging industry is set to grow by nearly 18% in the next year. This growth can be attributed to the fast development of the e-commerce sector and online shopping. As more products are being delivered to the doorstep, the demand for packages is also in the increase. IoT solutions can be used to automate certain processes in packaging manufacturing, which can reduce time, money, and human intervention. Digital labels can be affixed to packages to make tracking easy and efficient.

Application 17: Landslide Detection by IoT Application

Landslides are natural calamities that happen because of both human activity and natural phenomena. Landslides lead to loss of lives and property. Sensors can help determine soil moisture levels and soil movement, and send notifications with location details. The data can be analysed to predict possible landslides in a location. Preventive and precautionary action can be taken to prevent landslides, if possible or at least life and property.

Application 18: The Volume of Visitors Check by Smart Phone Detection

This application comes handy while monitoring large events where there is no limit to the number of visitors. IoT sensors can be placed at the entry, exit, and public transportation areas. The sensors collate data regarding the number of people and maximum people movement areas. This data can be analysed to calculate visitor’s volumes, average stay time, and people behaviour. The information can be used while planning other such events.

Application 19: Waste Management IoT Application

Waste management is a critical problem that governments all over the world are facing. There is so much waste being generated almost every day that managing it is a humungous task. IoT waste management involves setting up sensors on each bin placed in different locations across the city. When the waste is filled to a threshold level, a notification is sent to the connected device via Cloud. Based on the analysis of the notifications, the administrator can prepare a schedule for removing the waste from the bins.

Application 20: Urban Noise Detection

Noise pollution can be controlled by using IoT applications. Sensors can be used to detect noise levels in different parts of the city, and more so near hospitals, schools, and other regions. If the noise levels are higher than mandatory levels, then the requisite steps can be taken to reduce the noise.

Conclusion

IoT is bringing about a huge change in different sectors across verticals and horizontals. By properly using this emerging technology, we can change the shape of the future. Many leading companies have realised the importance of IoT and are investing in research and development in this field. The Internet of Things is a technology that is here to stay.

AWS vs Azure vs GCP-The IoT Rat Race

AWS vs Azure vs GCP-The IoT Rat Race

A defining IoT battle of our time is now between different cloud platform: Azure vs AWS vs Google and who will win the market. This is the three most popular IoT platforms used nowadays. But before knowing about these platforms, let’s discuss what led to the development of these platforms.

One of the major milestones in the field of technology is the emergence of IoT, as it opened up vast possibilities in the technology sector. Now have a look at some of the benefits you get in your day to day activities because of IoT.

  • It has made possible to bring the full power of the internet in varied devices, appliances.
  • It is because of IoT now you have homes with lightning, doors along with heating and cooling system that is controlled by Smartphones.
  • Then there are several Smartwatches and fitness bands that can easily monitor all your important statistics all over the day and makes you alert when something unusual occurs.

So, with so many benefits, we are required to make rapid IoT development, design good IoT devices. It also increases the amount spent on an IoT developer, so to decrease it various IoT platforms have been created. These platforms facilitate easy and quick IoT development. Thus, at present three popular IoT platforms are Azure, Google, and AWS. Let’s know in details about each of this platform:

  • Microsoft Azure: It is a Microsoft cloud solution that provides a good amount of cloud-based services like virtual machines, storage solutions, database management systems, messaging platforms and many more. The IoT platform offers several Azure services that can be used in IoT product development like downtime prediction, distant monitoring of IoT devices and easy integration with existing services. It is also cost-effective as compared to other IoT platforms.
  • Google: Google provides cloud computing services called Google cloud and its IoT platform called Google Cloud IoT platform. It is a little expensive than Azure but less than AWS. It is the third-largest IoT platform at present.
  • AWS: In the rat race, AWS is far in the lead. All IoT targeted features are present in the WS IoT platform. As compared to another platform it is little expensive.

Adopting cloud computing has rapidly become an important driving service for several businesses today when businesses are moved out from data centers to cut down costs and enhance agility. There were some early concerns on security and data sovereignty in these platforms which were later addressed by cloud vendors.

To know more about the IoT rat race between three platforms have a look at some of the points where we can compare them and it is easy to know which suits best for your organization.

  • Features and services offered: Which IoT platform to choose depends on the need of each customer and the payloads that are running. This also helps in knowing which platform leads. All three platforms AWS, Azure, and Google provide almost the same capabilities with reliable communication, networking, and storage along with auto-scaling, plus security and recognition management features.
  • AWS, Microsoft Azure and Google Cloud Platform offer largely similar basic capabilities around flexible compute, storage and networking. They all share the common elements of a public cloud: But still, AWS provides a large depth of services with analytics, networking, management tools, security, etc and leads the race.
  • Compute, database and networking and storage: For compute AWS offer EC2 instances that can be customized with several options. It also offers several other services like Elastic Beanstalk, EC2 container service, etc. Azure compute offering revolves around Virtual machines along with other tools like cloud services and resource manager that help in deployment of applications. Google’s Compute provides VMs in Google data centers. Similarly, for storage, Microsoft offers Azure storage service, Queue and file storage, Blob block storage along with site recovery, azure back up, etc. AWS storage includes simple storage, Elastic file system, Elastic Block storage, etc. All three platforms provide the best networking capabilities with automatic server loading balance. In the rat race, all three are at the same level in terms of computing, database and networking and also storage.
  • Customer deals: In terms of customer deals AWS leading the rat race, as it has taken a large consumer deals. It has successfully convinced most of the traditional businesses to move to the cloud.