“I’ve never played for a draw in my life” once quipped Sir Alex Ferguson, arguably soccer’s greatest coach. Considered by many to be greatest managers of all time, he has won 38 trophies, a record by any manager in the history of the world’s most popular game. Sir Alex was known to be astute while selecting his players and knew how to play to the strength of each to play to win.
Every investment that an enterprise makes on data or cloud is with an objective to win—win the mind and the wallet of the customer. However, recent data shows otherwise. An estimated total amount of 79 zettabytes of data is expected to be consumed globally by the end of 2021, which is up from 64.2 zettabytes in 2020. And the overall volume of data is only expected to increase.
To modernize infrastructure and fuel digital transformation, the digital world found its ally in ‘cloud,’ and this is transforming businesses like banking, retail, media, entertainment, and more. With the world at their fingertips, customer expectation is on the rise. However, despite making rapid strides in digital transformation, only 24% of organizations consider themselves as being data driven. Further, only 32% of organizations surveyed reported that they were able to realize tangible and measurable value from their data—indicating that these initiatives aimed at modernizing business have not met expectations.
This points to a chasm that exists between businesses and their data. With data being at the heart of all decision making, no enterprise can be relevant or competitive without all their data being understood across dimensions.The sheer volume, variety, and the explosive rate of growth of data can be daunting as enterprises embark on this journey.
Two foundational steps to bring the enterprise closer to their data
- The first step towards any data management initiative is to understand all your data, irrespective of its form or where it lies. IT environments have evolved, and businesses rarely have all their data in one cloud as a result. Hybrid and multi clouds are adopted as organizations work to mitigate risks and capture cost benefits.
- The second step would be to ensure your data stakeholders have the trusted and relevant data that you need to provide a service or enhance an experience. A bank would look to cross sell their services like loans or credit cards to their account holders. The heads of these departments would need to be provided with just the right level of data to offer these services. This would include past transactions, credit worthiness, possible financial needs or even ratings of services availed in the past from the bank or its competitors
Metadata, with its effective management enables an organization to comprehensively understand all data including its business context, lineage, and value. The complexity of today’s data landscape demands that metadata is managed with an AI-powered catalog, one that not only scans and catalogs the metadata but can deliver recommendations, suggestions, and help automate various data management tasks. Best-in-class data catalogs have a metadata knowledge graph that helps view metadata across multiple dimensions. The metadata knowledge graph also enables users to quickly search their enterprise data catalog using semantic search terms and keywords. Further, data can be discovered across multi-cloud and on-premises environments and holistic views gained across departments, facilitating data sharing and self-service. This holistic data view can reveal related datasets, tables, views, data domains, reports, and users—and aiding the progressive discovery of other datasets of interest.
Another key benefit that metadata management offers is its ability to equip business stakeholders with data that is trusted and governed. As organizations enter new businesses and engage customers through new business models, the role of data that is governed and trusted cannot be emphasized enough. With the understanding of the data that metadata provides, data governance can ensure that enterprises are able to deliver the right data to the right users at the right time.
So, because of its ability to provide context and understanding of all your data, metadata bridges the chasm between enterprise and its data. A world where data is burgeoning requires an AI-powered data catalog to manage the metadata and glean insights from all data. By understanding all the enterprise data regardless of its type or location, stakeholders are equipped with the data they need to either offer a service to their customer, ensure compliance, or improve operational efficiency.
So, if you feel that you are not part of the 32% who believe they are getting the full value of their data investments on cloud, it may be time to consider the steps outlined above. No game is ever won without a team playing to their strengths. And much like how a successful soccer coach decides the placement of his team based on his thorough understanding of his players, you need to be able to know your data well enough with all its complexities and nuances to know how it can be strategically deployed and the needed access given. This is what will differentiate those who get value from their investment and those who will not.
The race to the cloud is accelerating. As more workloads are migrated and with data volume growing rapidly in cloud data warehouses and data lakes, it is advisable that you consider a solution powered by unified metadata intelligence. This can bring together data cataloging, governance, quality, privacy, and democratization capabilities into a new, singular cloud-native service for data intelligence. Remember, leveraging your metadata would be what would make the difference between your success or failure when it comes to maximizing your cloud and data investments—and an AI-powered data catalog is crucial to win.
To learn more, I would encourage you to check out Informatica’s Cloud Data Intelligence Summit, where you can find sessions featuring our SMEs, analysts, and clients that can help you in your data journey.
Play to win!