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Use of Business Intelligence in Mobile App Development

We have come across the term “Business Intelligence” quite a few times in the tech world. So, what exactly does it mean? Business intelligence refers to an integrated software platform which find use in business data analysis and management. Many businesses use the BI app development to seamlessly analyze their data without the need for any IT involvement.

It all starts with AI. Artificial intelligence has completely revolutionized the modern era. Smartphones, which are now indispensable in our lives, stand a testimony. Many businesses are seeking out collaboration with mobile app development companies to design devices and apps with AI/ML technology.

In today’s blog, we will have a brief look at what mobile intelligence is. We will also look at its pros and cons and role in app development.

Mobile Business Intelligence: What it is

Mobile Intelligence refers to the mobile devices’ power to learn and adapt while analyzing and understanding user behavior. Today, many mobile apps have analytics tools and business intelligence in order to provide smart information to the end-user.

In simple terms, business intelligence means all the technology, applications and programs that store, retrieve, and analyze data. By using this, firms successfully deliver relevant services to the customer at any point of time.

Now, let us look at a few advantages of mobile BI.

Advantages Of Mobile BI

The first and foremost benefit is that it gives firms access to their data anytime, anywhere. Here, we discuss a few more benefits in greater details.

Information Collection

By integrating Machine Learning with your mobile apps, you can get data on a real-time basis. This will allow you to carry out multiple operations more efficiently and in lesser time.

Decision Making

If you have information with you all the time, you can easily carry out analysis using the right tools. With the analyzed data outcomes, businesses can make more informed choices and take better decisions.

Stay Ahead of Competition

Using business intelligence in mobile apps, you can easily make your business more responsive and flexible. It helps you to create a unique identity for yourself by reaching out to your clients on a real-time basis.

Improved Productivity

With real-time data, decision making becomes quicker. This means you have more of time left for executions which results in enhanced productivity.

Enhanced Customer Satisfaction

The main goal of any business is to make their customers happy with their services or products. When your performance is excellent and you exhibit increased productivity, you reach your customers faster. It also opens up chances to serve them better.

Difficulties Faced in Mobile BI

There are a few hurdles that might crop up in your way of mobile BI. Say for example, people in rural areas with poor network connections may not be that accessible to you. Also, scalability is a challenge in mobile BI. As you get more and more data, it starts affecting your service.

Besides this, one needs high-performance and stable hardware to run these programs. Such hardware could raise your initial costs .

Some popular BI Tools

BI tools are apps that collect and interpret huge unstructured data from various sources like websites, mobile apps, videos, emails, etc. They are not that effective as business analytic tools, but they are very helpful in drawing insights. With these tools, you can also build reports, dashboards, etc. These tools may bring together multiple data analysis applications such as online analytical processing (OLAP), operational BI and enterprise reporting. They may also include open-source BI, mobile BI, ad hoc analysis, and querying real-time BI, collaborative BI, etc.

Some common tools include

Google Analytics

Trustpilot

Databox

G2 Crowd

Zoho Analytics

Conclusion

With Business Intelligence, businesses of all sizes have gone truly global. Along the help of query building, analysis and data visualization, along with analytical report creation, many firms have reaped benefits of maximum return on their investments. With the right statistics, businesses are focused on developing apps that make them smarter, more efficient, productive, and have higher customer satisfaction.

EOV is dedicated to providing innovative mobile app development services to its clients from multiple domains. If you are looking for the right partner to build the app that your business truly deserves, get in touch with us now!

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5 principles of cloud native apps

We have all been hearing a lot about cloud native applications. But, what exactly does it mean and ho is it designed? Basically, cloud native architecture refers to adapting the new possibilities that cloud offers as against conventional on-premises architecture.

Cloud native apps do not need a lot of functional changes. However, they do require different non-functional changes and have greatly different architectural constraints.

In today’s blog, we will list down the main principles of this architecture for cloud native apps. These will help you reap benefits of the cloud server without falling in the loopholes of the old systems.

Principles for cloud-native architecture

So, basically the principles of cloud-native architecture focus on optimizing the system architecture. This will ensure unique capabilities, scalability and distributed processing for your cloud apps. This is something that traditional architecture may not achieve, at least that easily.

Let us look at the principles below.

Principle 1: Automating the infrastructure

While automating the software’s has always been a top choice, cloud has made it much easier now. With cloud, you can easily automate the infrastructure, as well as the associated components. Automating your infrastructure will surely help in enhancing the performance and resilience of your software systems. It will lead to faster deployment, quicker repairs, resulting in better outcomes for your products. Some of the common areas that you can aim to automate include infrastructure, CI,CD, monitoring and recovery etc.

Principle 2: Design more components to be stateless

To make things easier and hassle-free, your system architecture should be intentional. This is with regards to when and how you store state. It is wise to design more stateless components. Why? There are many benefits to designing stateless components. They are much easier to scale. For instance, to scale up, all you need to do is add more copies. Stateless components are easier to repair. You can simply terminate any failed component instance, and get a replacement, without any hassles. Also, load balancing becomes much easier in stateless components. This is because any instance is capable of handling any request.

Principle 3: Adopt managed services

With most of the cloud offerings, you do get a rich array of managed services. They provide numerous functionalities that completely off load backend management from your shoulders. Managed services greatly help in cutting down delivery times and operational expenses. The major types of managed services that you can consider include managed open source services, managed services with high operational savings and everything else in the third category. The first category is an easy choice since it comes with multiple benefits and little risk. Here, we have Cloud SQL or Cloud Bigtable.

Principle 4: Embrace defense-in-depth approach

Cloud native apps originate on the internet and always have the risk of external attacks. While traditional architecture care a lot for perimeter security, even it has unending risks and threats. Cloud native apps adopt a defense-in-depth approach by application of authentication between every component. It also minimizes the trust between components. You must take care to move beyond authentication and include other things. These include rate limiting and injection of script.

Principle 5 : Keep evolving, keep architecting

When it comes to cloud native apps, one of the core characteristics is that they are always evolving, including their architecture. You should aim to continuously refine, improve and enhance the architecture of your system. This updation has to be in sync with organizational changes, IT system upgradation and so on. Though, it requires repeated investments, it will ensure that your systems are updated for better reliability, scalability and performance.

Conclusion

What we would like to mention here is that the above principles are essential, but they are not any magical solutions for cloud native architecture. However, following these principles will surely help to get you the most out of the cloud. If you are looking for building any cloud native applications or software for your business, please get in touch with us for the same! Our experts are well-versed with the different principles of optimized cloud architecture and will help build you scalable and responsive products within the promised timeline.

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Microservices Scalability With Kubernetes

Kubernetes is considered to be a good choice as a platform for deploying the Microservices. You can develop, build, test, deploy, and scale the components of a microservices-based application independently. Kubernetes has containers that enable the portability of the application components and easily get integrated into a larger application.

The applications you build on microservices can be scaled in various ways. You can scale them to support development with the assistance of larger development teams and can be scaled to perform better. There are several advanced ways to tackle performance issues. In this blog, we will cover some easy techniques to scale the microservices by leveraging Kubernetes:

Vertically scaling the entire cluster Horizontally scaling the entire cluster Horizontally scaling individual microservices Elastically scaling the entire cluster

Let’s check each of these techniques one by one.

Vertically scaling the cluster

As your application grows, a point might come where the cluster doesn’t have enough compute, memory or storage to run your application. As you go on adding new microservices or replicating the existing microservices for redundancy. Just max out the nodes in your cluster. Then, monitor this through your Kubernetes dashboard. Now, increase the total amount of resources that are available for the cluster. Either use vertical or horizontal scaling when scaling microservices on a Kubernetes cluster.

As we grow our application, we might come to a point where our cluster generally doesn’t have enough compute, memory or storage to run our application. As we add new microservices (or replicate existing microservices for redundancy), we will eventually max out the nodes in our cluster. (We can monitor this through our cloud vendor or the Kubernetes dashboard.) Scale up the cluster by increasing the size of virtual machines (VMs) in the node pool.

Horizontally scaling the cluster

Apart from scaling the structure vertically, you can also scale it horizontally. Don’t change the size of the VMs, it can be of the same size, just that you can add more VMs. As you add more VMs to the cluster, you can easily spread the load of your application across different computers. Horizontal scaling is less expensive as compared to vertical scaling.

Horizontally scaling an individual microservice

As an individual microservices become overloaded which can be monitored in the Kubernetes dashboard. So, when a microservice becomes a performance bottleneck, horizontally scale it to distribute the load properly over multiple instances. You can also scale individual microservices for performance and horizontally scale the microservices for redundancy. You can also create a more fault-tolerant application. With multiple instances, there are always others available to pick up the load in case any single instance fails. This further allows the failed microservice instance to restart and start working again.

Elastic scaling for the cluster

Now, talking about elastic scaling it is a technique where you can automatically and dynamically scale your cluster. This will help your cluster to meet different levels of demand. During the low demand, Kubernetes automatically deallocates the resources that aren’t required anymore. And, when the demand rises, new resources are allocated to meet the high workload demands. This saves up the cost because you only end up paying for the needful resources required to handle the application’s workload. You can also use the elastic scaling at the cluster level to grow the clusters automatically that are close to their resource limits. In conclusion, elastic scaling works by default, but there are several ways in which you can customize it based on your requirements.

When you use microservices it gives you granular control over your application’s performance. You can easily measure your microservices’ performance to look for the ones that aren’t performing properly, are either overworked, or are overloaded due to high demand. In such cases using the Kubernetes dashboard to figure out the CPU and memory storage for your microservices is highly recommended.