The topic of data integration has been around forever. Before we used technology to manage data, we integrated data in manual ways. At the time, we needed to integrate simple data structures such as customer data with purchase data. As the industry progressed, we have gone from managing flat data files and integrations to using applications to creating databases and data warehouses that automates the integration of data. The early data sources were few compared to today, with information technology supporting almost everything that we do. Data is everywhere and captured in many formats. Managing data today is not a small task but a much bigger job and grows exponentially every year.
What is Big Data Integration?
Data integration is now a practice in all organizations. Data needs to be protected, governed, transformed, usable, and agile. Data supports everything that we do personally and supports organizations? ability to deliver products and services to us.
Big data integration is the practice of using people, processes, suppliers, and technologies collaboratively to retrieve, reconcile, and make better use of data from disparate sources for decision support. Big data has the following characteristics: volume, velocity, veracity, variability, value, and visualization.
- Volume ? Differentiates big data from traditional structured data managed by relational database systems. The number of data sources is much higher than the conventional approach to managing data inputs.
- Velocity ? Data source increases the rate of data generation. Data generation comes from so many sources in various formats and unformatted structures.
- Veracity ? Reliability of data, not all data has value, data quality challenges.
- Variability ? Data is inconsistent and has to be managed from various sources.
- Value ? Data has to have value for processing; all data does not have value
- Visualization ? Data has to be meaningful and understood by a consumer
Integration of big data needs to support any service in your organization. Your organization should run as a high-performing team sharing data, information, and knowledge to support your customers? service and product decisions.
