The possibilities of data analytics solutions and big data tools are manifold and new applications of the technique are being discovered across various sectors. The software development industry is one such area where the data analytics solutions and strategies are ushering paradigm-shifting changes.
1.The rise of Native Apps
The number of smartphone users reached 3.8 billion in 2021 and this growth has incidentally fueled the dominance of Native Apps. By the end of 2022, the number of App downloads is projected to cross 258 billion and these figures prove that large volumes of data are being generated. Big data allows mobile app developers to derive insights that equip them to develop innovative and futuristic apps. Developers now rely on big data tools to gather, assess and streamline data sets which helps them substantially to address patterns in client preferences. Machine learning along with data analytics solutions proffer unique, focused and unparalleled experience to the users.
2.Transition to Cloud Services
Cloud computing has become indispensable for developers to meet the needs of modern software consumers and to stay ahead of the competition. It helps developers to access vital resources such as multiple testing and staging servers with the cloud system, thereby enhancing the speed of software development, efficacy of software testing and improving productivity.The increasing business demands and accumulation of large volumes of raw data calls for cloud services for scalability and recovery.
To put it simply, the data-driven approach has inspired software developers to employ cloud services as it provides easy access to large volumes of data and testing environments, enabling faster turnaround time for software development.
3.Self-Service Analytics Tools software
There is an increasing demand for self-service software analytics tools. Gone are the days when businesses relied on IT departments to manually create reports and visualizations. Self-service Analytics tools empower the end-users to generate reports and visualizations instantly. It enhances data visibility, puts data & decisions in better context and eliminates the need for a data scientist to make sense of the data.
As more businesses are becoming data-driven, more data-centered software and tools are becoming the need of the day.
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4.App-centric to Data-centric
The traditional app-centric architecture of software development requires custom access controls, multiple data copying efforts and lengthy integration projects. Every time a new software or app is to be made or any improvement or new solution is introduced, developers are forced to execute system integration and data copying repeatedly.
Putting data at the center of software development frees the developers from such redundant practices. Data-centricity offers a single source of truth; it does not require copying as the data is no longer tied to a particular application. This empowers developers by allowing data reuse and eliminating data silos.
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