Publications

Publications

Title: Bridging Data Silos Using Big Data Integration


 

Abstract:

With cloud computing, cheap storage, and technology advancements, an enterprise uses multiple applications to operate business functions. Applications are not limited to just transactions, customer service, sales, finance but they also include security, application logs, marketing, engineering, operations, HR and many more. Each business vertical uses multiple applications which generate a huge amount of data. On top of that, social media, IoT sensors, SaaS solutions, and mobile applications record exponential growth in data volume. In almost all enterprises, data silos exist through these applications. These applications can produce structured, semi-structured, or unstructured data at different velocity and in different volume. Having all data sources integrated and generating timely insights helps in overall decision making. With recent development in Big Data Integration, data silos can be managed better and it can generate tremendous value for enterprises. Big data integration offers flexibility, speed, and scalability for integrating large data sources. It also offers tools to generate analytical insights which can help stakeholders to make effective decisions. This paper presents the overview on data silos, challenges with data silos and how big data integration can help to stun them.

 

Keywords:

Data Silo, Big Data, Data Pipelines, Integration, Data Lake, Hadoop


Journal: International Journal of Database Management Systems


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Title: Overcoming Data Silos Through Big Data Integration


 

Abstract:

With cloud computing, cheap storage and technology advancements, an enterprise uses multiple applications to operate business functions. Applications are not limited to just transactions, customer service, sales, finance but they also include security, application logs, marketing, engineering, operations, HR and many more. Each business vertical uses multiple applications which generate a huge amount of data. On top of that, social media, IoT sensors, SaaS solutions, and mobile applications record exponential growth in data volume. In almost all enterprises, data silos exist through these applications. These applications can produce structured, semi-structured, or unstructured data at different velocity and in different volume. Having all data sources integrated and generating timely insights helps in overall decision making. With recent development in Big Data Integration, data silos can be managed better and it can generate tremendous value for enterprises. Big data integration offers flexibility, speed and scalability for integrating large data sources. It also offers tools to generate analytical insights which can help stakeholders to make effective decisions. This paper presents the overview on data silos, challenges with data silos and how big data integration can help to overcome them.

 

Keywords:

Data Silo, Big Data, Data Pipelines, Integration, Data Lake, Hadoop


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