Modern data integration: A must-have for the data-driven enterprise
Agility and real-time insights have quickly become the keystone of the data-driven enterprise. And for good reason, according to Gartner, by 2022 companies will be valued on their information portfolios.
It goes without saying that being able to move data at the speed of change makes the difference between a successful business and one that falls short.
As organisations continue their digital transformation journeys, adopting modern technologies such as the cloud and data lakes, it's important they also embrace a modern approach to data integration.
In 2019, IDC predicted the sum of the world's data will grow to 175 zettabytes in 2025—a 61% compounded annual growth rate. Considering this exponential growth of data, for many businesses modern data integration may seem too steep a mountain to climb—but in reality, the climb isn't as tough as it may appear.
By collecting and interpreting multiple datasets, modern data integration eliminates information silos, democratising data access and providing a consistent view to users. This in turn helps create agile, integrated data environments that enable companies to respond faster to change, better leverage new technologies and develop innovative products and services.
Enter DataOps
Modern data integration has become a catalyst for a new breed of data operations (DataOps). DataOps is an emerging set of practices and technologies for building data and analytics pipelines to meet business needs quickly. As these pipelines become more complex and development teams grow in size, organisations need better collaboration and development processes to govern the flow of data from one step of the data lifecycle to the next—for example, from data ingestion and transformation to analysis and reporting.
DataOps was born from the need for a new methodology that would encompass the adoption of modern technologies and the teams using the data. It leverages real-time integration technologies, such as change data capture (CDC) and streaming data pipelines, to ensure data is readily available for use, typically in a self-service model or integrated with current systems.
As a result, DataOps streamlines how data owners, database administrators, data engineers and data consumers interact, as they all use data to improve decision-making and achieve business goals.
Bringing IT and the business together
DataOps allows organisations to gain insights—and ultimately, take action—quicker than before by continuously processing new data, monitoring performance and producing real-time insights. However, users should have full visibility of the data they're using, including when, where and by whom it has been modified, making data catalogues the backbone of DataOps.
After data has been created, extracted, transformed and integrated, a data catalogue informs users of available datasets and metadata on a specific topic, providing assistance in locating data required to build analytics. Essentially, a data catalogue is an inventory of data that enables users to glean accurate and trustworthy critical business insights. It holds information on the datasets, offering quality assessment scores for critical factors relevant to users—for example, whether the data is clean, if it's being used by other teams, and so on.
A leading global pharmaceutical company, Astellas Pharma US, realised its data warehouse simply couldn't keep up with the business' data needs. In order to stay on the leading edge of an industry built on innovation, it invested in Qlik Data Catalyst to accelerate and simplify data functions. In less than 12 weeks, they deployed a governed data platform, moving data closer to users through a secure, managed data lake. This gave teams immediate self-service, on-demand access. The platform automatically loads, encrypts, organises and validates prepared datasets, enabling the analysis of 100 billion records from 50+ data sources. The results speak for themselves; Astellas:
• Achieved 30-fold increase in total projects the marketing analytics team could deliver
• Reduced time required for marketing analysts to get new datasets for analytic research projects from six months to one hour
• Eliminated 50% of the IT system costs associated with the data management platform
• Gave 60+ analysts self-service access to data, expanding their ability to find the data they need and collaborate, interpret, enhance and apply data to high-value business challenges
More than ever, organisations need to build on modern data infrastructure and leverage DataOps to achieve a more holistic and agile approach to data. It is now easier than ever to transform raw data into a governed, analytics-aware information resource with both speed and scale. Qlik strives to do just that with its Data Integration Platform.
A modern data management solution should drive more insights and value from data, enabling better decision-making and transformation across the entire organisation. By leveraging modern data integration, businesses can gain a competitive advantage to build an agile and future-ready enterprise.
