The interactive relationship between data and AI is propelling businesses into a transformative era. Over 250 million organizations are leveraging or exploring AI in their business operations. However, many companies struggle to extract meaningful business value from these advanced technologies. The missing piece of the puzzle? – A comprehensive data and AI governance framework. That’s where a pioneering solution like Databricks steps in. In this blog, we explore the best business advantages of Databrick’s Unity Catalog. We’ll also go over the relation between data and AI, the meaning of a forward-focused data governance strategy, and how it helps businesses keep pace with the evolving data landscape.
The data and AI interaction: How it works
Without data, AI technologies would have nothing to learn from, and without AI, your data would remain untapped potential. Together, they create a powerful synergy that drives business success. Let’s say you have a retail company, and you want to improve sales forecasting. Here’s how data and AI will interact to ensure your growth:
- You collect and store various data sources, including sales records, inventory data, and other external data.
- AI algorithms can process this data to clean, organize, and prepare it for analysis. For instance, they might fill in missing values, identify outliers, and create structured datasets.
- AI models, such as ML algorithms, use this processed data to develop predictive models. They leverage historical sales data and other variables to forecast future sales.
- Most importantly, the AI models continuously learn and adapt as more data becomes available, helping your organization make more accurate predictions over time.
- AI-driven sales forecasts provide valuable insights and allow you to optimize inventory management and marketing strategies, resulting in increased sales and reduced costs.
Understanding the potential of modern data governance
Outdated approaches to data governance can pose significant challenges for businesses. For instance, consider a financial institution that relies heavily on traditional, manual methods to assess credit risks for loan applicants. The methods may fail to leverage the vast amount of data available with the institution. Furthermore, obsolete governance practices can result in delayed loan approvals, missed opportunities, and increased risk of defaults.
In contrast, a modern approach to data governance would involve modern data analytics and machine learning techniques to process and analyze different data sources, including social media activity and online purchase history. This modern approach can lead to more accurate and timely credit assessments, enhancing the organization’s competitiveness in the market.
Some of the best advantages of implementing modern governance practices:
- Ensures that your data is accurate and consistent, resulting in more reliable insights and decision-making.
- Enables better customer profiling and service personalization.
- Helps navigate complex data regulations, reducing legal risks and protecting sensitive information.
- Encourages innovation by providing easy access to data and promoting AI experimentation.
- Supports scalable AI initiatives.
- Mitigates the risks of breaches and data loss via robust security measures.
Why choose Databricks to govern data and AI
The Databricks Lakehouse Platform seamlessly blends the strengths of data lakes and data warehouses, enabling you to optimize cost-efficiency and accelerate the realization of your data and AI objectives. Databrick’s Unity Catalog stands as a groundbreaking solution, pioneering unified governance for data and AI within the lakehouse framework. The innovative solution empowers you to seamlessly oversee diverse datasets, including structured and unstructured data, machine learning models, dashboards, and files across various clouds and platforms. Data scientists and engineers can securely explore, access, and collaborate on trusted data and AI resources.
Image source: Databricks
Let’s take a quick look at some of the best business advantages of Databricks Unity Catalog:
1. Get a unified perspective on your data and AI assets
Discover and categorize structured and unstructured data, machine learning models, and assorted files across multiple cloud platforms. You can bring all your data sources together, including MySQL, PostgreSQL, Amazon Redshift, Snowflake, Azure SQL, and Google’s BigQuery, within a singular hub. With a single-entry point for data exploration, it becomes easier to comprehend and extract insights.
2. Enable simplified data access
Databricks provides you with a single permission model for both data and AI assets. The unified interface allows you to create and enforce access policies across various data and AI resources. This further ensures consistency and auditability, regardless of the cloud or platform you’re operating on. Databrick’s Unity Catalog enables you to level up data security via low-code, attribute-based access policies.
3. Supercharge data operations with AI-driven monitoring
With AI at the helm, you can automate the monitoring process, swiftly diagnose errors, and uphold the quality of your data and ML models. The real business advantage emerges through proactive alerts that automatically identify PII and address issues with data and AI pipelines. Also, you can leverage automated column-level data lineage to streamline debugging process, impact assessment, and more. Get built-in system tables, covering billing, auditing, and lineage. It enables businesses to derive invaluable insights that empower better decision-making, cost management, and compliance adherence.
4. Facilitate new collaboration levels with open data sharing
Databricks enables you to expand your data and AI reach across cloud, regions, and platforms through seamless integration of open-source Delta sharing. The integration enables you to secure collaboration with global partners, clients, and stakeholders, facilitating fresh revenue opportunities and driving enhanced business value. There’s no need for exclusive formats, complicated ETL procedures, or resource-intensive data replication.
5. Perform seamless integrations with existing systems
It’s time to bid goodbye to costly migration processes. The Unity Catalog effectively interfaces with your current data catalogs, data storage systems, and governance solutions, allowing you to maximize the value of your data operations.
Wrapping up
Databricks offers an exceptional platform for data analysis within a lakehouse environment, and its userfriendly interface empowers your business to address data challenges with confidence. As a valued member of the esteemed Databricks partner network, LumenData is dedicated to helping you develop a data strategy that harnesses Databricks’ cutting-edge capabilities. Initiate a conversation with us to modernize your governance approach today.
Reference links:
Authors:
Shalu Santvana
Content Crafter
Ankit Kumar
Technical Lead
Ankit Kumar
Technical Lead
Shalu Santvana
Content Crafter
