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Big Data and Software development Combine for Digital Transformation

big data and software development digital transformation

Drowning in data isn’t the same as big data. Both big data and software development are used to power digital transformation in today’s high demand and continuous technology evolution.

As a phrase, big data and big data analytics is being abused and overused by marketers. It isn’t having a ton of data, it is about the combination of structured data with unstructured data to acquire new insights that in the past weren’t possible. Big data analytics software has changed the game for small and big businesses alike. Rather than using small focus groups and general demographics for extrapolating the target market activities, contemporary companies could now access specific information and plenty of it, regarding customers and employees, which help fine tune sales and marketing as well as drive increased ROI.

Big data and digital transformation

Digital transformation helps organizations embrace a culture of change and stay competitive in the worldwide market. Big data enables companies to make strategic, meaningful adjustments, which maximize results and minimize expenses. A digital transformation is not complete unless a business will adopt big data.

Regardless of the proven value of gathering raw software project data and analyzing it to build easily digested, actionable key performance indicators, a lot of enterprises continue to struggle for extracting, analyzing and organizing data into reports, let alone scorecards of dashboards.

Identifying the goals

Some organizations read or hear about the kinds of data that other companies use in their own digital strategies. This must never provide yours with a beginning point to pursue big data apps. Every business is unique and requires strategically looking at short and long term goals. With a list of challenges and goals, organizations could begin to break down big data to usable insights, which would drive success. Begin small, and avoid using non-specific goals, like ‘maximize the bottom line’. Rather, consider overcoming pointed challenges and meeting objectives to:

  • Boost employee workflow for better productivity.
  • Improve or change customer experience.
  • Retain clients.
  • Identify customer pain points in the digital space for marketers to focus.
  • Lower costs.

While producing accessible, accurate information, like defect reports will not guarantee software quality, without them it is almost impossible to achieve it. To improve the situation, several companies have developed or integrated into current platforms the functionality that keep tabs and organize data that’s related to software team activities.

The connection between big data and software development

Processing sets of data of over five petabytes, particularly those integrating unstructured data from numerous sources, need extremely fast processors, coupled with sophisticated software analysis for identifying associations and patterns that offer meaningful feedback. Furthermore, companies should have a mechanism for visualizing the information. In the past ten years or so innovative organizations developed technologies, such as software development tools, to accomplish the goals and wrap them to analytics platforms that already is revolutionizing decision making that is fact-based in other areas. While a software development activity may look like a world away from big data, it shares some notable similarities with big data that are unstructured. It could not be accessed easily, natively nor properly organized for analysis and reporting.

Data analytics, conceptually is as much a human observation and phenomenon regarding volume, as it is on reflecting any specific purpose or value in the data itself. To put it simply, data is generated, gathered and stored at an ever-growing rate. Data being amasses at exponential rates. Analytics is all about turning the huge pile of data to something useful. Moreover, analytics attempts to find useful and meaningful patterns among data as well as actionable insights to the industry jargon.

Benefits of data analytics

Leveraging big data in organizations yields many associated benefits, such as:

  • Timeliness – Sixty percent of every workday, knowledge workers spend trying to find and manage data.
  • Accessibility – Half of the senior executives report that access to the right data is hard.
  • Holistic – Currently, information is kept in silos within a company. For instance, marketing data could be found in mobile and web analytics, social analytics, testing tools, email marketing systems and more, each with a focus on the silo.
  • Relevance – Forty-three percent of organizations are not satisfied with the ability of their tools to filter out unimportant data. Something as streamlined as filtering customers from web analytics could offer a ton of insight to acquisition efforts.
  • Trustworthiness – Twenty-nine percent of organizations measure the monetary cost of poor quality data. Monitoring several systems for customer contact information updates could save millions.
  • Security – The average breach of data security costs $214 for every customer. The secure infrastructures built by big data hosting and technology partners could saw an average company of about 1.6 percent of yearly revenues.
  • Bad or outdated data results in 46 percent of enterprises making bad decisions that could cost billions.
  • 80 percent of companies struggle with numerous versions of the truth, depending on data source. By combining vetted, numerous sources, more companies could product intelligence sources that are highly accurate.

Data analytics plays a big role in software development. As the requirements continue to evolve and new technologies are being created, software systems and cloud storage will become be more relevant.


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