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As a global trend, technology has enabled businesses to collect an unprecedented – and vast – amount of data related to their business. Today, customers engage with businesses in a myriad of ways, generating data from websites, business applications, social media pages, chatbot interactions, mobile devices, blogs, and other documents. When an organization has the right tools, this wealth of data can inform business intelligence (BI).

Isn’t it about time you got some valuable answers from all that latent information laying around your organization?

Moving From a Pile of Data to a Plethora of Insights

Brace yourself: some jargon and terminology are coming.

Technology has advanced enough to enable the discipline of Machine Intelligence, which essentially enables a machine to translate a massive data set (by way of analytics) into an output that is meaningful for human beings.

First, there is the broad bucket of Artificial Intelligence (AI). Within this, a machine is now capable of Deep Learning and Machine Learning, whereby the computer learns and expands its abilities over time. Let’s pause set aside some AI myths. While an AI can help humans perform their jobs more efficiently, it’s unlikely your custom software development is going to eliminate your human staff.

Instead, this robust computing technology enables skilled professionals to receive the output from the data and take action – instead of wasting days, or even months, trying to make sense of an insurmountable amount of data.

When these mega data sets are analyzed and presented in a report, summary, or graph, the power business intelligence (BI), which informs strategic and tactical decisions. Through a system of BI, organizations can ask questions and have them answered with their information systems.

Big Data Applications

What kind of questions are businesses asking Big Data to answer? Here are 3 key questions big data is answering today:

  1. How do we improve customer engagement and retention?

Real-time data can enable individualized services, specific to an individual customer. Grocery retailer Kroger uses Big Data to inform its customized loyalty programs, collecting data from an estimated 770 million consumers to help boost loyalty. According to the retailer, 95 percent of its sales use loyalty cards, and this data has helped drive a $12 billion revenue incremental and seen a 60 percent redemption rate. Kroger has employed this solution for more than a decade, launching it in 2005 and leveraging it through the 2009 recession.

  1. How do we increase operational efficiency?

Thanks to the Internet of Things (IoT), in the retail sector and other industries, businesses can also glean information about the machines powering their operations. (Quick reminder: the IoT is a connected network of machines. You can learn more here.) Automotive company Tesla employed Big Data to power research and development that support car maintenance. As a result, IT, engineers, and the supporting manufacturing lines can resolve issues and provide fixes with its software.  Analyzing the data from the sensors on its vehicles allows Tesla to streamline performance and preempt maintenance issues.

  1. How do we reduce waste?

Analytics can also generate insight into issues that, if left unresolved, can become more costly. Telecommunications provider Sprint set out to reduce network error rates and customer turnover by using analytics to drive more capacity and preempt issues before they become larger problems requiring expensive repair work.

Big data is poised to arm any industry – from aviation to media to healthcare – with better information that can improve customer engagement, increase efficiency, and reduce waste. Organizations just need to make sure they’re putting the right tools in place.

Putting the Right Tools in Place: Effective Software Solutions for Big Data

Like any technology, whether it’s cutting edge or established, it takes a quality, expertly designed solution to unlock value. A first step in developing the right software to harness your big data is understanding the difference, and relationship, between BI and Big Data.

Business Intelligence (BI):

As organizations harness Big Data, it’s likely they will unlock areas to hone in on for ongoing BI. It’s important to also consider which tools are necessary to maximize insights from Big Data. Some considerations include:

  • Should you focus on infographic software development, to help streamline visualization for stakeholders?
  • Do you need to prepare for any technology transformations within your organizations, such as future IoT technologies or additional AI applications?
  • Do you have the IT talent in-house, or should you explore nearshore development services or IT outsourcing models to develop your software solutions?
  • What kind of measures need to be implemented to ensure security, today, and in the future?

Most organizations have a wealth of data just waiting to be put to use, but moving from disparate data to streamlined insights can be a tasking exercise without the expertise to handle not only the software development, but all the QA usability testing, security considerations, and forward-thinking that should be considered to implement an effective solution for the long term.

Our Genies have helped our clients build effective tools to maximize big data. Whether through a nearshored or offshored team of savvy IT professionals, our top talent engineers can spearhead infographic software development that delivers informative, intuitive outputs, equip organizations to harness their people data with a robust AI-powered analytic tool, or power insights through an Internet of Things in the retail sector.

Learn more about the services TechGenie can provide to help your organization get some answers from your Big Data: https://techgenies.com/services/.