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The Intersection of Software Development and Big Data for Digital Transformation

dhrumitshukla profile image Dhrumit Shukla ・3 min read

In the dynamic and fast changing world today, every company would want to stay ahead of the competition or at least be at par with competitors. This is only possible if businesses have the right systems and strategies in place. Custom software apps automate and simplify the processes in an enterprises, thus saving a great amount of money and time while boosting efficiency.

CUSTOM APP DEVELOPMENT SERVICE PROVIDERS
There are many custom software developers these days that develop applications to meet client requirements with big data analytics integration. Data analytics is being overused and abused by marketers. It is not about having a ton of data, it’s about the combination of structured and unstructured data to gain new insights that were not possible in the past. Data analytics software change the game for both small and big businesses alike. Instead of suing small focus groups and general demographics for extrapolating target market activities, modern organizations now could access particular information and plenty of it, regarding employees and customers that help fine tune marketing and sales and drive increased return on investment as well.

The digital transformation helps companies embrace a culture of change and remain competitive in the global market. Data analytics enable organizations to make meaningful, strategic adjustments that maximize results as well as minimize expenses. Digital transformation isn't complete unless a business adopts huge data.

CONNECTION AND INTERSECTION OF LARGE DATA ANALYSIS AND SOFTWARE DEVELOPMENT
Processing data sets of more than five petabytes, especially those integrate unstructured data from several sources, requires really fast processors, along with sophisticated software analysis to identify patterns and associations that offer meaningful feedback. Moreover, organizations must have a mechanism to visualize information. In the last decade or so, a cadre of innovative companies developed technologies, like software development tools to accomplish goals and wrap them to analytics platform that are revolutionizing decision making that’s based on fact in other areas. Although a software development activity may appear a world away from huge data, it shares some noteworthy similarities that is unstructured. It could not be easily accessed, natively nor properly organized for reporting and analysis. In concept, data analytics is as much a human phenomenon and observation about volume, since it is on reflecting any specific purpose or value in a data itself. Simply put, data is generated, gathered and stored at an ever increasing rate. Data is amassed at exponential rates. Analytics is all about turning a great pile of data so something useful. Furthermore, analytics attempts in finding meaningful and useful patterns among data and actionable insights to the industry jargon.

DATA ANALYTICS ADVANTAGES
Leveraging data analytics in organizations yield different associated benefits, including:

  • Accessibility. Half of senior executives report that accessing right data is difficult.
  • Timely. Sixty percent of each workday, knowledge workers spend attempting to look for and manage data.
  • Relevant. Forty-three percent of companies aren’t satisfied with the ability of their tools to filter out irrelevant data. Something as simple as filtering customers from web analytics can provide a ton of insight to acquisition attempts.
  • Holistic. Information at present is kept in silos within an organization. For example, marketing data can be found in mobile and web analytics, testing tools, social analytics, marketing systems and more, each with a focus on silo.
  • Secure. The average data security breach costs $214 for each customer. The secure infrastructures made by huge data hosting and technology partners can saw an average company around 1.6 percent of annual revenues.
  • Trustworthy. Twenty-nine percent of companies measure the monetary cost of poor data quality. Monitoring various systems for customer contact information updates can save millions.
  • Authoritative. Eighty percent organizations struggle with many versions of truth, depending on the source of data. By combining numerous, vetted sources, more companies can produce intelligent sources that are very accurate.
  • Actionable. Outdated or bad data could result in 46 pe5rcent of companies making bad decisions that can cost billions of dollars.

It can be said that data analytics plays a huge role in developing software solutions. As the requirements continue evolving and new technologies are being made, software solutions and systems and cloud storage will be more relevant. Data analytics make sense to developers because it creates value out of a big perceived waste. Persistent data is a cost to store and value extraction out of it makes plenty of sense. Data analytics is one of the core pillars of the network effect, which comes from client-server services. The hugeness of data obviously comes from data source size, that’s often correlated to the size of a business. If the big source of data is appropriately leveraged, it builds a barrier for new market entrants.

Posted on Oct 11 '17 by:

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Dhrumit Shukla

@dhrumitshukla

Dhrumit Shukla has been working as Business Development Manager in a software development company named TatvaSoft since 5 years.

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