Big data integration, as the name suggests, involves extracting data from disparate sources, combining them, and then analyzing them to get valuable insights. Albeit sounding simple, it is a complicated process that processes and stores huge datasets that can be structured, unstructured, and semi-structured. A primary focus of big data integration is to present data in novel and unique ways. Integrating your business’s internal datasets with industry data can be make-or-break for some establishments. To make that data usable, coherent integration processes are a necessity. 

Statista predicts that the volume of data created worldwide will exceed 181 zettabytes and that this massive spike in data production will lead to the global big data analytics market to produce annual revenue of $68.09 Billion, all by 2025. Companies worldwide are now depending on big data integration to help them make key business decisions, and this trend will just continue well into the future. This article takes a closer look at the benefits that come along with big data integration and the challenges that stop it from being fully adopted.

The Benefits

A recent study by Forrester Research revealed that most companies only analyze a mere amount of 12% of the data they have, and thus are massively missing out on key customer insights hidden within the remaining 88% of data. Big data integration comes into play in such scenarios and can help companies tap into data hordes that were previously ignored. Here are a few of the other benefits that big data integration offers 

  • Elevated market intelligence: Analyzing big data can help brands deepen and broaden their understanding of market dynamics. A prime example of this can be witnessed in the case of social media. E-marketer recently reported that the amount of time an adult spends on social media everyday is at 95 minutes, the highest its ever been. Social media is a major source of market intelligence for almost all product categories. For any commercial transaction, there are hundreds of people out there sharing their opinions via social media, and these shared opinions are invaluable for marketers. 
  • Smarter Audience Targeting: The predictive analysis for recommendation engines has evolved exponentially since the advent of big data. These new and improved recommendation engines are built on sophisticated customer insights so that they can be more sensitive to demographics and customer behaviour. Big data integration can help deliver better recommendations, not only to e-commerce websites but also to a whole plethora of sectors, so that they can get better sales while ensuring a greater quality in output.
  • Better Customer Insights: IBM reported that In 2020, every person generated 1.7 megabytes per second. This massive influx of data plays well into the strengths of big data integration. Big data integration can help businesses get better customer insights by analyzing data from various sources such as traditional sources of customer data, such as purchases and support calls, external sources, such as financial transactions and credit reports, social media activity, computer cookies, etc. This is arguably the most important benefit that comes from adopting big data integration and has proven to be invaluable in upscaling businesses and brands.
  • Improved Business Operations: Big data integration helps businesses optimize processes to generate cost savings, boost productivity and increase customer satisfaction. Better fraud detection, risk management, and cybersecurity planning help organizations reduce financial losses and avoid potential business threats. Big data analytics can also help improve physical operations. The combination of big data and data science can alert predictive maintenance schedules, hence helping reduce costly repairs and downtime for key equipment and systems. The advantages of Big Data Integration are now being widley adopted and is evident as the the Vantage reported that 97.2% of organizations worldwide are investing in big data and AI.

 

The Challenges

The true discussion when it comes to integrating big data is one of the tangible resources vs. monetary cost. An IBM study recently reported that 90% of total data in the world today has been created in the last two years alone. With data constantly evolving and being produced at an alarming rate, there is a need to manage trends and assess them for integrity, to ensure that the data being received is timely and relevant for decision making. This is a major hurdle in big data integration. Other challenges for big data integration include

  • Synchronization: The chances of desynchronization amongst data coming in wide ranges of sources using different schedules and rates are high. Since data are from a wide range of sources, by the time a dataset gets integrated, another might become out of the syncing schedule and thus be termed as old. Thus, in big data integration, variations in data management, extraction, and transformation will create discrepancies in data synchronization.
  • Skilled Data Analysts: The need for skilled data analysts and big data engineers has never been higher. Developing workflows and drawing actionable insights from the processes is no easy task, and lack of skilled labour can become a potential challenge to the process of big data integration. 
  • Security Troubles: The significance of big data in companies and corporations worldwide cannot be understated, and subsequently ensuring security in big data integration can not be ignored. Big data integration is likely to face numerous security-based challenges as data sources are not always well-known and also create lethal breaches. Ensuring confidentiality in big data integration should be a priority.
  • Choosing the Right Framework:  Incompatibility between Big Data Management tools can cause problems. NoSQL refers to a collection of different data management frameworks. Different NoSQL approaches opt for varying paradigms including the key-value store concept that enables them to connect with the entities in the data sets. Each NoSQL approach varies one from one another, with some claiming greater evolvability, scalability, and performance output. The existence of such a large variety actually harms big data integration and the range of NoSQL tools has caused some confusion regarding the compatibility of different approaches. Choosing the right one can indeed be a challenge for those looking to employ big data integration.

 

Why Choose Intone for Your Big Data Integration?

Big data integration can help your business understand customers better and also approach prospective consumers proactively. Intone is a proud and trusted provider of state-of-the-art big data integration solutions to various industry leaders and pioneers. We offer:

  • A data integration strategy that works across multiple platforms 
  • A data integration strategy that performs processing of critical data in real-time.
  • Tracking devices with Internet of Things (IoT) sensors that perform various functions such as enhancing operational efficiency, reducing risk, and yielding new insights and analytics
  • Intone’s solutions offer improved operational efficiency, increased flexibility, and scalability, reduced operational costs, and increased revenue.
  • Integrating our solutions can help you achieve Faster time-to-market along with better internal communications.

 

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Image by Gerd Altmann from Pixabay

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