Until now, the management and use of data in the digital transformation of enterprises has not provided much convenience for employees, especially compared to the experience that employees get when they use it to search for information, or use Dianping to search for their favorite restaurant.
As consumers, we have high expectations for data discovery and choice. We want our network to provide a wide catalog of information that makes it easy for us to retrieve and categorize information and find what we want quickly. However, to this day, the breadth of information we obtain in our work is still not at the level of the above-mentioned **.
So, has anything changed? Many organizations are helping their employees more easily discover and access secure, trusted, and high-quality enterprise data so they can use it to identify new opportunities to solve problems, innovate, and increase revenue.
Data is a core element of digital transformation, and if employees struggle to find the right data they need, their digital transformation initiatives will fall short.
Enterprise data is often scattered across hundreds of cloud and on-premise systems, including traditional transactional databases, electronics, cloud-based marketing systems, and data lakes. The emergence of new data sources and applications (e.g., IoT, artificial intelligence, etc.) adds to the complexity of the data environment.
Whether it's improving the customer experience, providing analytical insights for decision-making, or moving your business to the cloud, it all depends on your employees' ability to track relevant data and understand its quality and source. And, according to many experts, conservative estimates suggest that the amount of data in enterprises will double every two years, and the challenges will become more complex.
In fact, much of the data that should be valuable is underutilized, or even not utilized, as companies embark on ambitious digital transformation initiatives.
Shervin Khodabandeh, Partner and Managing Director at The Boston Consulting Group, noted:"Most agencies only use a very small fraction of the data they have access to. While they are constantly collecting and storing terabytes of data, in my experience, less than 5% of them are actually being used. ”
Ideally, business users and IT users should search for enterprise data as easily as they can use and Dianping search. Also, users should be able to see how other users feel about it and use it as a reference.
In order to do this, we need to catalog and classify enterprise information in some logical way to achieve "popular" use of information. That is, to make the information available to business users, data scientists, application developers, and other business personnel. Semantic search enables self-service access for business analysts in non-technical departments, just as consumers filter retail items by brand, color, and other attributes. Users should also get context on the data, including who the data, who it is associated with, and what the quality of the data is, in order to understand and trust the data.
Users can search for results no matter where the data is in the enterprise, because the search operation is driven by the Intelligent Data Catalog, a technology layer that involves inventory data and gives users access to inventory data stored in the cloud and on-premises. Artificial intelligence and machine learning make data catalogs "smart", with auto-labeling, extreme accuracy, data similarity analysis, and lineage definitions. Most importantly, in the digital age, it can meet the needs of enterprise data management in terms of speed, processing scale, automation, and insights.
The Eckerson Group, a research and consulting firm, noted in a report:"In today's world, data management is an unwise and impractical practice without a data catalog. We are rapidly entering a new era where communication, collaboration, and crowdsourcing will be the pillars of data management. ”
Without consistent, comprehensive, and accurate data, there are many areas where digital transformation goals cannot be achieved, such as:
Build a foundation for advanced analytics. Data scientists typically spend 80% of their time looking up data, compared to 20% of their time on artificial intelligence, machine learning, and modeling. Data Catalog inverts this ratio by quickly discovering and accessing data, helping data scientists and business analysts leverage trusted data to deliver the insights they need for data-driven decision-making.
Create a complete, customer-centric experience. Data resides in every corner of the business, and if you want to be customer-centric, it's important to have a 360° view of all your data sources. By identifying all the major elements of customer data, a data catalog provides the foundation for more personalized interactions and a better customer experience.
Empower seamless cloud data migration. Now, the myth of the security and cost of legacy systems has been completely shattered, and most organizations, including medical institutions and institutions, have begun to move towards the cloud. However, migrating an on-premises data warehouse to a cloud-based alternative environment such as Amazon Redshift, Google Big Query, Microsoft Azure SQL Data Warehouse, and Snowflake is not as easy as flipping a switch. Data cataloging helps architects understand the data landscape for the first time, assess data quality, select the right data to migrate, and understand the downstream impact, ultimately accelerating the modernization of cloud data warehouses.
Ensure data governance and data privacy. If a business doesn't understand what data it has, where it resides, and how it's allowed to be used, it won't be able to meet existing and upcoming data security and privacy regulations. The data discovery capabilities provided by a data catalog are critical to identifying and managing data under governance controls and building trust in customers, employees, and other key stakeholders.
Digital transformation can take many forms, including customer-centric business models, IoT and AI projects, employee enablement, task-based and data-dependent projects, and a variety of projects are on the agenda of CEOs and boards around the world. Intelligent data management capabilities based on the Enterprise Data Catalog establish the foundation for digital transformation to help enterprises survive and thrive in the face of constant change.