New Software Development Initiatives Lead To Second Stage Of Big Data
New software development initiatives have lead to the beginning of the second stage of big data. Read more to learn about what that can mean.
The big data market is expected to be worth $189 billion by the end of this year. This is over a 50% increase in just four years. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another.
New software is making big data more viable than ever. As new software development initiatives become more mainstream, big data will become more viable than ever.
Software Development Remains a Driving Force of Big Data
We are living in a data-oriented world where everyone seems obsessed with Big Data. Whether it’s in the banking sector, health, communication, marketing, or entertainment, Big Data has permeated every aspect of our daily lives. In the modern business world, data forms the foundation upon which businesses gain insights about their customers and the business environment to make correct decisions.
Relevant, complete, accurate, and meaningful data can help a business gain a competitive edge over its competitors which is the first step towards scaling operations and becoming a market leader. As such, any company looking to stay relevant both now and, in the future, should have data management initiatives right.
Although many organizations seem not to understand the intrinsic value of Big Data, an equal number seems to in different industries seems to be adopting this concept. In fact, according to a recent survey conducted by Gartner Survey, it is estimated that 75% of companies are planning to heavily invest in Big Data in the decade.
Some of the areas that seem to be at the forefront of adopting Big Data is software and web development industries. The emergence of massive data centers with exabytes in the form of transaction records, browsing habits, financial information, and social media activities are hiring software developers to write programs that can help facilitate the analytics process. Moreover, developers themselves are using predictive analytics in their software development processes.
to rapidly find and fix bugs faster, significantly lowering the software development rates.
In this article, we are going to look at how software development can leverage on Big Data. We will also briefly have a sneak preview of the connection between AI and Big Data.
What is Software Development?
Software development simply refers to a set of computer science-related activities purely dedicated to building, designing, and deploying software. The software itself is a set of programs or instructions that command a computer on what to do.
There are three basic types of software. They include:
System software provides core functions like OS, disk management, hardware management, utilities, and other operational necessities.
Programming software helps developers with tools such as compilers, linkers, text editors, debuggers and other coding tools, all of which are necessary for the entire software development life cycle.
These are applications that assist users to perform specific tasks. A good example of application software includes data management software, office productivity suites, security programs, and media players.
Before we look at the role of software development in Big Data, let’s briefly take a look at the different types of Big Data.
This is an organized set of data that can be processed, stored, and retrieved from a database in an orderly format using a simplified search engine algorithm. For example, you can organize an employee table in a database in a structured manner to capture the employee’s details, job positions, salary, etc.
Unstructured data lacks a specific format or structure. As a result, processing and analyzing unstructured data is super-difficult and time-consuming.
Semi-structured data contains a mixture of both structured and unstructured data. Simply put, it contains important information although it hasn’t been profiled under a particular repository.
Characteristics of Big Data
There are three fundamental parameters used to define the characteristics of Big Data i.e Variety, Velocity, and Volume.
In the past, the primary source of data was mainly spreadsheets and databases. Fast forward to today, data is mainly collected from a wide array of sources including emails, photos, social media posts, PDFs, videos, audios, and so much more.
Velocity refers to the real-time speed at which data is created. Basically, it comprises of both the incoming and outgoing data sets at different speeds. For instance, the velocity of Youtube video uploads is 1 video every second.
As the name suggests, Big Data deals with huge data volumes mainly generated from various different sources like business processes, machines, social media platforms, human interactions, networks, etc.
Role of Software Development in Big Data
Each one of us contributes towards the generation of data in the form of images, videos, text messages, documents, emails and so much.
So, how can software development helps you take advantage of Big Data?
Below, we have laid down 5 different ways that software development can leverage Big Data.
The efficiency of a software development team is a key determinant of the success of a project. With the data analytics software, development teams are able to organize, harness and use data to streamline their entire development process and even discover new opportunities. As a result, businesses are able to get solutions that help them make smart business moves, improve efficiency, and improve customer satisfaction.
Software development has made great strides in terms of saving thanks to Big Data. For instance, technologies like cloud-based analytics and Hadoop helps in storing large data amounts which would otherwise cost a fortune.
In the software development world today, failure is an acceptable norm. However, no developer wants to fail or even realize that their application has been rendered irrelevant by time after spending many months on it. As such, agility is one of the requirements of a modern-day developer.
With Big Data technologies, any software development company, is able to gather the necessary data in real-time, which is then incorporated in agile software development concepts to come up with adaptive delivery approaches. These approaches operate under the assumption that validation must be carried out as soon as possible consequently minimizing exposure risk as in the course of any project.
Data integration is key for any business looking to keep abreast with the ever-changing technology landscape. As a result, companies are heavily investing in creating customized software, which calls for data integration.
One of the primary elements of data integration and analytics in software development is having good data. With Big Data, software developers are able to look into completed projects, extrapolate intel, and to create a platform upon which new projects can be built on. Aside from that, digital data integration helps companies make a strategic and meaningful adjustment which is key in sustaining a competitive culture.
Real-Time Data Processing and Delivery
As it turns out, Big Data, processing, analysis, and storage is super-complicated, especially for big enterprises. Unfortunately, big enterprises looking to exploit the benefits of Big Data often have to deal with the challenge of creating and maintaining an efficient, stand-alone solution that can handle huge unstructured data volumes.
Fortunately, software developers are using AI and machine learning to develop corporate-wide analytics solutions that can effectively and efficiently handle humongous amounts of structured and unstructured data in real-time. In the event a problem occurs, development teams are able to see the problem and handle it before it gets out of hand.
Most automated code analyzing machines can only do so by just extract snippets of a software. The only problem with this is that it looks at similar historical problems and how it may have been solved.
The good thing about Big Data is that it goes way beyond the historical patterns to giving test engineers and developers the underlying problem and how it can be resolved. As a result, timely corrections are done hence reducing the overall development cycle even if you are working with a remote development team.
The Connection Between AI and Big Data
Big Data and AI are the two frontiers which have been touted as the mechanical giants that will change the way we do everything in the future.
As it turns out, Artificial Intelligence and Big Data will empower machine learning technology by continuously reiterating and updating the existing data banks. As a result, we will have entire business process autonomously operate without any human intervention.
Although these two frontiers are in their novice stages, with time, they will help businesses realize the exact customer’s needs and devices ways to implement changes to match these needs as they change.
Big Data and software development are slowly but rapidly becoming intertwined. Together with a host of other disruptive technologies like mobile computing, social networking, IoT, and cloud computing, Big data is augmenting interactions, creating immense opportunities, and shortening development life cycles. As software demands continue to mature, Big Data will continue to be at the center of providing efficient, transparent, and scalable technologies that companies can use to solve sophisticated problems.
And with the growth of IT outsourcing, companies shouldn’t have a problem in acquiring the qualified personnel with the right skills to build big data applications.
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