A data catalog helps organizations organize, discover, and manage their data assets effectively. Explore how data catalogs streamline data governance, improve data quality, and enhance decision-making with best practices, implementation tips, and real-world case studies from Secoda’s customers.
Read Part 3 of our series on Data Quality Score. Learn how to implement Secoda’s Data Quality Scores (DQS) to enhance data quality, streamline processes, and drive better decision-making. Follow these actionable steps to secure stakeholder buy-in, define policies, and leverage automation tools for optimal data management.
In Part 2 of our series, learn how Secoda's Data Quality Score evaluates stewardship, usability, reliability, and accuracy to drive better data governance, with actionable insights for improving data management practices and benchmarks.
As we step into what’s next for data teams, it's not just about welcoming LLMs into our toolkit; it's about recognizing the shift they represent. It's a move towards democratizing data, breaking down barriers, and automating tasks and workflows that can drive tremendous impact
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With the right data catalog, companies can better understand and manage their data. However, it can be daunting to choose from the myriad of options available when you’ve decided to implement a data catalog in your stack. That’s why we’ve created this simple step-by-step guide that will help you assess your data catalog needs and select the right one for you
Cloud data governance ensures secure, compliant, and efficient management of cloud-stored data, enhancing data quality and mitigating risks for organizations.
Starting with data lineage is critical for a successful cloud migration. It provides insight into how data flows through an organization and helps address challenges such as security and data integrity. Data lineage tracks the flow of data and identifies the systems, applications, and processes that handle it. By following best practices such as automation and utilizing your data lineage, you can make the most of your investment and optimize other areas of your business.
o you need to migrate data from Oracle to another platform? The data migration process might seem daunting, but following the right steps can ensure a seamless and frictionless migration. In this blog, we’ll provide you with a step-by-step process for migrating data from Oracle, along with some general information about data migration.
Secoda AI is the first data discovery solution powered by LLM. With a chat-based interface, think of it as ChatGPT for your data stack. It lets anyone, regardless of technical ability, answer any data question at the speed of thought.
In today's data-driven world, businesses are increasingly adopting cloud-based solutions to optimize operations and extract valuable insights from their data. In this guide, we will outline the key steps for migrating your on-premises data infrastructure to Snowflake.
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Secoda is a data catalog tool that makes it easier for your teams to search, access and understand data. Data discovery is intuitive when using Secoda, even for non-technical users. With our platform, you can consolidate all of your organization's data knowledge in one secure place. This eliminates data silos and inconsistencies while also making your data easily searchable. Users can find the data they need as quickly as they can do a Google search.
Data teams can be challenging to lead even when they’re well established and you’ve been working with them for a long time. Inheriting a data team can pose all of those well-known challenges and many others. While it can be intimidating to take on a data team that already has its own way of working, these challenges can be overcome with the right strategy.
A data lake is a repository for big data sets that don’t have a set structure. Data warehouses are databases optimized to perform analytical queries. Relational databases are databases optimized to query current, consistent, accurate and complete sets of data.
After working with hundreds of data teams, we believe there are five key factors that help can help you determine whether or not your data team is high performing and that you can do to help your data team transform into a high performing team.
If you're looking for a job as a data analyst, then you've come to the right place. I'll walk you through preparing for interviews and offer some tips on how to make yourself stand out from other candidates. We'll talk about what skills are required for this role, what questions an interviewer might ask during the interview process, and how to show that you're qualified for the job if it happens to be one of your dream positions in life.
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Data Enablement comprises everything that contributes to improving data teams' workflows. With good Data Enablement practices, even teams with the most archaic data stack can operate efficiently. Without good Data Enablement tools, even the most modern data stack won’t help.
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As an early data hire at a fast-growing company, one of the first things that you’ll likely encounter is a backlog of questions from employees. This backlog, alongside all the other tasks associated with reporting, maintaining data and creating new pipelines can feel extremely overwhelming.
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