Big Data Solution Based on multiple cloud services in the Microsoft Azure Ecosystem

The way businesses operate has changed thanks to big data dramatically. Big data platforms are used by many businesses to improve the performance of their PR staff, increase ROI on their marketing strategies, and maintain a high reputation with consumers. As more app developers incorporate big data technology in their apps, there have been significant changes in the mobile app development market.

The first is the unprecedented growth potential for the mobile app ecosystem. Everyone is connected to their mobile phones. Therefore, companies are naturally inclined to invest in mobile application development to target their prospects.

How can you increase the ROI of your app development efforts? Big data and analytics can be used to make informed and intelligent decisions. This data is used to develop mobile applications.

Benefits of Big Data Solutions for Business

Everyone has heard about Big Data and its boom in the industry. It's a topic that is constantly in the news. Companies from all sectors of the economy are using Big Data to encourage data-driven decision-making.

Big Data is now gaining popularity in many areas, including healthcare, education, and governance. Nearly every organization and enterprise, large or small, has already taken advantage of Big Data.

Gartner states that "Big Data" is high volume, high velocity, and high-variety data assets that need new processing methods to enhance decision making, insight discovery, and process optimization.

Customer Acquisition and Retention

Organizations must be unique in how they market their products to stand out. Companies can use big data services to pinpoint the exact needs of their customers. As a result, they can establish a solid customer base from the beginning.

Big data analytics can track consumer behavior. These patterns are then used to build brand loyalty. Amazon has perfected this technique, which offers one of the best shopping experiences online today. These suggestions are based on your past purchases and consider items you have purchased, browsing habits, and many other factors.

Identification of Potential Risks

Businesses are now thriving in high-risk environments. However, these environments require risk management processes. Big data has been instrumental in the development of new risk management solutions. In addition, big data can help improve risk management models' effectiveness and develop more innovative strategies.

Complex Supplier Networks

By using big data, companies can offer their supplier networks (also known as B2B communities) more precision and insight. As a result, big data analytics allows suppliers to overcome the constraints they often face. In addition, big data analytics allows suppliers to access higher levels of contextual intelligence, which is crucial for their success.

Supply chain executives see data analytics as a disruptive technology. As a result, they are changing the foundation of supplier networks to include high-level collaboration. This collaboration allows networks to apply new knowledge to solve existing problems and other situations.

Why Business Should Consider Microsoft Azure Platform?

Microsoft Azure Cloud is a growing set of cloud services that enable organizations to store and manage data, build complex web apps, and improve cybersecurity and compliance.

Azure is a public cloud platform that allows users to scale up their infrastructure to meet their specific needs quickly. Users can also create hybrid computing environments. In addition, Azure integrates with businesses and allows them to create, manage, and deploy custom web applications using the tools and frameworks they are most familiar with.

With this in mind, here are some of the best business benefits to Microsoft Azure.

On-demand scalability

Business needs change over time, whether for growth or downsizing, making scalability a core concern for any infrastructure-related investment. Microsoft Azure's public cloud platform allows organizations to expand their storage space and computing power as needed, providing maximum capacity for short-term surges of traffic or long-term expansion projects. In addition, Azure is designed to scale with businesses. Users can adjust their service agreements to avoid disruption to their high-load applications.

Cost-Effective Subscription Models

Microsoft Azure's usage-based pricing structure allows small and large businesses to manage their IT budgets more effectively and take advantage of the cloud features they require. This usage-based pricing model effectively lowers infrastructure costs, reduces the IT management burden, and streamlines cross-departmental workflows. In addition, Microsoft's 24-hour support team and extensive knowledge base are available to users in case of any problems.

High availability

Unlike many other cloud service providers, Microsoft Azure offers high availability and redundancy across its data centers. Microsoft Azure is well-suited for companies with global reach as it operates in 55 countries and has access to 140 more. Microsoft's massive presence allows it to offer a service level agreement that guarantees 99.95% availability. This amounts to less than 4.5 hours per year.

Building an Awesome Big Data Solution on Microsoft Azure

To build a big data solution, you must address the following issues: data collection, storage, analysis, visualization, and others. These requirements can be met exclusively through Azure services or via a combination of Azure services and third-party integrations. In addition, there are many pre-built, fully-managed significant data-as-a-service options available through the marketplace. These include Cloudera, Qubole, and Cazena.

Big Data solutions require a range of tools. These include technologies that deal with data sources, integration, and data stores. They also include technologies that help create data models and present them through visualization and reporting.

Microsoft Azure offers a complete solution covering all aspects of building and managing a Big Data solution. However, this solution can only be built on Azure if various complementary technologies are used. They all work together to create a complete Big Data offering.

Data Sources

Data sources are the foundation of any Big Data solution. To process the consolidated data, it is necessary to source large amounts of data to build a Big Data solution.

Data sources can come from any source, and they can be either structured or unstructured. Let's use the real-time traffic management software as an example. Data sources include:

• Video surveillance data.

• Sensor data on the road network.

• GPS data from vehicles that use the road network.

Big Data solutions require a large amount of data from many sources to build accurate models.

Integration and Data Storage

Once the data sources have been identified, they must be processed and stored. Azure offers many integration options and data storage solutions that can address the various requirements of Big Data solutions. Each Big Data solution is unique and requires a specific set of technologies to match it.

Microsoft Azure HDInsight, a Microsoft Big Data solution, is a 100% Apache Hadoop-based Azure cloud service. This cloud service is fully managed, making it easy to process large amounts of data quickly, efficiently, and economically. It also allows you to use popular Big Data open-source frameworks such as Spark, Hive, and R.

HDInsight combines both data storage and integration services to create Big Data solutions. It is the preferred platform for these types of solutions. It is a native cloud solution available worldwide and has all the required security and compliance measures. You can also use various productivity tools, including Microsoft Visual Studio, Eclipse, IntelliJ, and Scala. It supports R, Java, and.Net platforms.

Data Models and Analytics

After the Big Data solution's data storage, integration and services have been defined and implemented. The next step is to analyze the data using data models and analysis.

Azure offers a wide range of analytics services, including over 50 dedicated artificial intelligences, analytics, and IoT. One would never use all 50 services for a particular Big Data analysis solution. Big Data solutions are a collection of technologies that can create a platform. The type of analysis you do with the collected data will determine which analysis service you use.

Azure Analysis Services, Microsoft's enterprise-grade analysis engine, is available as a service to provide generic analysis services. For example, Log Analytics can collect, search and visualize machine data from both on-premises or cloud services, while Stream Analytics analyses real-time data streams coming from IoT devices. Azure Databricks is the best choice if you need an Apache Spark-based analytics platform. Data Lake Analytics can run large parallel processing programs in many coding languages and store petabytes in Azure Data Lake.

Visualization and Reporting

You will need the visualization and reporting platform to complete your Big Data solution. There are many options for Big Data solutions, so you should choose the one that best suits your needs.

Azure and Microsoft have several visualizations and reporting tools. Either display reports with SQL Server Reporting Services or extracts the data displayed in Microsoft Excel. If you want to create business intelligence dashboards, you can also use Microsoft Power BI. All of this could be displayed through Microsoft SharePoint Online or on-premise.

The Key Takeaway

Moving your data to the cloud is a great way to maximize the value of your extensive data analysis. Azure offers you the flexibility to transfer many of your processes over directly, use an all-in-one solution, or combine the two.

This article should have given you some insight into setting up Azure-based analysis. However, it also gave you an idea of the resources available, regardless of whether or not your expertise is in this area.