Modern Data Integration: The DataOps Catalyst
Agility and real-time insights have become the holy grail of the data-driven enterprise. In an increasingly competitive environment, being able to move data at the speed of change makes the difference between an ultimately successful business and one that falls short.
The ongoing shift to modern architectures such as cloud, data lakes and streaming technologies, require a modern approach to data integration. However, with the volume of data increasing exponentially, this integration often becomes a daunting task.
Fortunately, modern data integration addresses these concerns. By collecting and interpreting multiple data sets, it eliminates information silos, democratizing data access and provides a consistent view to business users. Due to its ability to unlock the value of an organization’s data assets, modern data integration has become a catalyst for a new way of data operations.
DataOps was born from the need for a new methodology that would encompass the adoption of modern technologies and the teams working and using the data. DataOps is not something that can be aquired or bought, it is a strategy that helps organizations to advance the speed and accuracy of analytics and improve productivity.
By leveraging real-time integration technologies such as change data capture (CDC) and streaming data pipelines, DataOps is disrupting how data is broadly shared and how it is made available across the enterprise. Furthermore, this methodology has a large impact on the collaboration mentality inside an organization, as it requires a cultural transformation as communcation is one of the pillars in which DataOps stands.
DataOps streamlines how data owners, database administrators, data engineers and data consumers interact, as they are the ones utilizing the data to improve decision-making and ultimately achieve their business goals.
The convergence between IT and Business
DataOps helps accelerate cycle times while improving performance and reducing the time to insight. However, to take full adavantage of DataOps, business users must know where their data comes from at all times, as well as when, where and by whom that data has been modified.
This is where data catalogs become essential. After the data has been created, extracted, transformed and integrated, a data catalog informs users about the available data sets and metadata around a specific topic, assisting in locating the data they need to build their own analytics.
Simply put, a data catalog is an ‘inventory’ of data that allows users to understand and trust critial business insights. It acts as a marketplace that holds information about data sets and offers quality assesment scores for critical factors users should know. For example, whether the data is clean, if it is being used by other teams or if it addresses specific policies.
Enterprises, more than ever, need the ability to build on modern data architectures and DataOps to achieve a more holistic and agile approach to data. Attunity, a division of Qlik, and Qlik Data Catalyst strive to deliver a platform that expands the ability to transform raw data into a governed, analytics-aware information resource with both speed and scale.
Ultimately, a modern enterprise data management solution should drive more insights and value from data, enabling improved decision-making and transformation across the entire organization. By leveraging modern data integration, businesses can take full advantage of DataOps to build an agile and future-ready enterprise.