The data landscape is changing and growing rapidly. Data has become the new competitive battlefield of our time. As a result, many organizations today are committed to become “data-driven.” However, leading organizations seem to be failing in these efforts.
The 2019 Big Data and AI Executive Survey published by NewVantage Partners revealed the percentage of organizations identifying themselves as being data-driven has been steadily declining from 37.1% in 2017 to 32.4% in 2018 to 31.0% in 2019. Furthermore, the survey which comprised of 64 C-level business and technology executives from organizations like American Express, Ford Motor, GE, GM, Johnson & Johnson, etc. mentioned 72% executives stated that they have yet to forge a data culture while 53% stated that they are not yet treating data as a business asset.
Organizations need to turn their data assets into revenue and profits. And the first step in any data-driven digital transformation initiative is to manage your data as an enterprise asset: take inventory of it, assess its value, and maximize its use—just like you do with any significant investments and resources.
In today’s organizations data is diverse and distributed across many different departments, applications, and data warehouses and data lakes (some on-premises, others in the cloud), making it a challenge to know exactly what data you have and where. Further, the lack of visibility into the movement of data across the data supply chain can be overwhelming. With the increase in the number of data sources, types and formats, the data landscape becomes even more complex.
Consider the following challenges that occur due to such circumstances:
Build a single source of truth of your organization’s data – A data catalog helps you address all the above problems and beyond. A data catalog creates and maintains an inventory of data assets through the discovery, description, and organization of distributed datasets. The data catalog provides context to enable data engineers, data scientists, data stewards, data/business analysts, and other lines of business data consumers to find and understand relevant datasets for the purpose of extracting business value. A data catalog is essential to business users and decision makers because it synthesizes all the details about an organization’s data assets across multiple data dictionaries by organizing them into a simple and consumable format. Turning enterprise data into a competitive advantage requires business users to be able to easily access, understand, and use trusted, clean, high-quality data across the enterprise.
Before embarking on a data catalog evaluation, you must figure out what you want to accomplish with one. Data catalog tools are exciting because they can democratize data across an organization. However, data is only meaningful to decision makers if it is enriched with context, which comes from people and metadata. Connecting data to its context is the difference between making the right or wrong decisions with data. For example, when using the imperial versus metric systems and using the wrong unit definition to hang a shelf might not seem to be a big problem. However, to NASA, that gap in understanding cost $125 million in 1999.
To address such complexities more and more organizations today are embracing Artificial Intelligence (AI) and machine learning models with the power of cloud that are helping them make informed business decisions, create competitive advantage, and accelerate digital transformation. According to a leading analyst firm, there is a growing demand for cloud capabilities, connected data architectures, metadata and the automation of routine and nonroutine tasks through application of AI.
These five capabilities help ensure you can make the most of your enterprise data.
Informatica Enterprise Data Catalog (EDC) is an AI-powered data catalog that provides a machine learning-based discovery engine to scan and catalog data assets across the enterprise—across multi-cloud and on-premises. Powered by the CLAIRE® engine it provides intelligence by leveraging metadata to deliver recommendations, suggestions, and automation of data management tasks. Informatica EDC enables both business and IT users to easily discover and understand relevant and trusted data with powerful semantic search, end-to-end data lineage, automatic domain discovery, integrated data quality and profiling statistics, holistic relationship views, intelligent recommendations, and an integrated business glossary. Informatica EDC integrates with Informatica Intelligent Cloud Services (IICS) data management services that provide critical capabilities for cloud data warehouses, data lakes, and lakehouses. IICS Cloud Data Integration provides high-performance ETL, ELT, data ingestion, synchronization, and replication for multi-cloud environments. Learn how Informatica has been helping organizations achieve:
It’s harder than ever to manage data today, as organizations collect huge volume of data from many heterogeneous sources (like ERP, CRM, streaming devices, SaaS applications, etc.) generating data in real-time with different qualities. While a basic Data Catalog can help however an Intelligent Enterprise-Class Data Catalog allows you to discover, understand and trust data across:
Organizations using an intelligent enterprise-class data catalog are able to scan tens of millions of records, catalog hundreds of data sources, correlate thousands of business terms in minutes (versus days or weeks) and discover end-to-end data lineage in seconds (versus days, weeks or even months).
If you want to gain end-to-end visibility, find any data with a simple search, and use data you can trust, watch this video to learn how Informatica can help: