Data collection is essential for research and data analysis. Learn more about the most popular data collection models and techniques here.
Learn more about the top data migration tools used by growing tech companies so you can streamline your data migration and ensure everything goes smoothly.
Data orchestration is becoming more prevalent in many industries, and data orchestration technology is evolving at a rapid pace. See the current trends here.
Whether you’re designing an onboarding plan for your data team, or if you’re starting a new role yourself, you’ll be able to apply these actionable insights to shorten the time it takes to get up to speed. Learn more
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.
How To Conduct On-Premise To Cloud Migration
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.
With Secoda, data enablement leads can ensure that their data is secure, compliant, and governed by company-wide policies.
What does fast fashion, data debt, spring cleaning and Monk has in common?
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.
Data enablement allows organizations to harness the power of their valuable data. Learn how to implement data enablement in your organization and more here.
A data governance policy is a set of rules, procedures and guidelines that define how an organization collects, stores and uses data. Learn more here.
Data observability tools are becoming increasingly important components of data stacks. Discover the top data observability tools used by tech companies here.
Data orchestration involves managing and processing data in an organization to make it available when and where it's needed. Learn about the benefits here.
Metadata governance is a critical component of any successful data management process. Learn more about metadata governance in this comprehensive guide.
Metadata management tools are essential for the successful management of metadata. Discover which metadata management tool is right for your organization here.
Metadata management tools are essential for the successful management of metadata. Discover which metadata management tool is right for your organization here.
Discover how to plan out your metadata schema and manage your metadata effectively so you can take your organization to the next level. Learn more here.
Metadata standards are the foundation for an effective data governance strategy, as they allow for consistency and enable effective data sharing. Learn more.
Metadata is defined simply as data about data and is a powerful tool for organizations. Learn everything you need to know about metadata in this guide.
Metadata management provides organizations with a way to structure, organize and secure data according to their data governance policies. Learn more here.
Discover the top data reverse ETL tools used by growing tech companies and learn more here.
Organizations can use ETL tools to easily format and store data between systems. Discover the top data ETL tools used by growing tech companies and learn more.
Data dictionary tools can help you centralize your data repository, define information related to your data, and more. Discover the top data dictionary tools.
Data lineage tools are a great tool for any tech company’s data stack. Discover the top data lineage tools used by growing tech companies and learn more here.
Are you already in a data-driven field or thinking about becoming a woman in data? Check out these tips for success from successful female data professionals.
Integrate Salesforce with Secoda to save yourself countless hours troubleshooting data in your Salesforce environment. See all field references in your entire organization and go to market faster than ever.
The goal of data privacy is to keep personal, sensitive and important information safe and secure. There are many myths about data privacy. Learn more here.
A data mesh help organizations create a more resilient, scalable and easy-to-understand data infrastructure. Learn more about data mesh and how to build one.
Metadata is data that provides information about other data. Learn about the types of metadata that are relevant for data teams and which matter most.
Modern data teams are focusing on privacy, governance and more. Here are data trends you can expect to see this year and how they can benefit your business.
Secoda AI is the first AI suite of search, catalog, lineage, and documentation solutions, powered by LLM
Data teams face a variety of challenges with a traditional data warehouse. Learn what these are and how to overcome them with modern data warehousing.
Active metadata is data that defines data to create a single source of truth. Learn more about active metadata management and the benefits for data teams here.
Edit your data dictionary, data documentation, data catalog, or data cataloging together with support for real-time multiplayer editing
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.
Ever wonder what BI tools other teams are using? Below is the overview of the top 5 BI tools based on over 250 data teams data stacks in 2023
Metadata descriptions about your data, like what type of data it is and whether or not it’s missing values will help you understand better why your pipeline failed.
If you’re looking for a solution for remote data knowledge management, choose Secoda. Our modern data catalog tool makes it easy for your teams to manage, search, and discover data.
Data democratization allows all employees to have access to company intelligence. Learn more about data knowledge and how to democratize your data here.
With one accessible repository, you can combine data knowledge and discovery in one centralized, easy-to-manage location. Data teams and nontechnical users will have speedy access to all of the data they need.
Discover the best data and analytics tools for startups. Learn more about what kinds of tools you should add to your modern data stack and tips for success.
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.
Data debt is a species of technical debt that is created when teams don’t catalogue, clean and categorize their data
it is possible to automate end-to-end data lineage using the right tools. This allows companies to avoid manual processes, reduce the risk of errors, and save time and money in the long term.
Data management is a complex, multi-faceted process. It's not enough to just collect data; you need to be able to store and manage it effectively too.
Vanity metrics are metrics that look good but don’t actually give you information on how to make your business better. They’re easy to measure, which is why they get tracked so often. It's also easy to understand them, since they're usually pretty straightforward.
Introducing: the new way to build your company data portal
Data governance tools are a great tool for any tech company’s data stack. Discover the top data governance tools used by growing tech companies here.
Data analysts are responsible for collecting, cleaning, analyzing, and reporting information about the data stored in databases
We're excited to introduce our new Fivetran integration for Secoda that lets you see how sources are brought into your data warehouse
Data teams help startups understand key metrics and growth opportunities. Discover how to succeed as the first data hire at an early-stage startup here.
How to find the best data onboarding tool for your team and why this is essential for scaling companies.
How to document your data quickly and efficiently using Secoda.
Why the current data tooling market fails to truly democratize data discovery within a company, and how to find a tool that your business and product teams will actually be able to use.
How to manage fast growth as a data team in a fast growing company
What are the responsibilities of a Data Engineering Manager? Tooling, scaling the team, communications, and mentorship.
Great Expectations is a data validation framework and platform. Learn how to integrate Great Expectations with Secoda and improve your data quality here.
Data lineage is a process for tracking the evolution of data as it flows from source to destination. It makes it possible to understand the connections between different data sources.
An increase in data literacy results in less questions and hand-holding from the data team, easier data discovery, and better data hygiene.
Data engineering is integral to all of the functions of a company. Here are 5 best practices data engineers should follow.
Data documentation is a description of anything in a company’s data knowledge such as tables and metrics. Learn how to automate your data documentation.
A data council is a team dedicated to improving outcomes, ensuring strategic alignment, holding people accountable and setting up a cross-functional forum.
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.
All about the new Secoda and Hightouch integration and how to get it set up!
Secoda can now be synced with a Git repository, letting you customize how you develop and deploy Secoda and help your team adhere to application development lifecycle best practices.
The future of the modern data stack will continue to make it easier than ever to extract even more value from your data. It’s an exciting time to be a data geek, and I’m happy to be riding this wave.
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.
How to Create A Data Catalog, A Step-by-Step Guide
Knowledge sharing in analytics is sharing business context surrounding particular code, metrics or data
Data literacy is the ability to go beyond merely reading data. Learn how to increase your team’s data literacy and make data easier to access
The data NPS can help data teams understand the impact of their work to enable self-service and have a good pulse on what they can do to improve the data product.
Data Product Manager: The role and best practices for beginners
Data discovery tools should be comprehensive in the data knowledge that they capture
Because there is so much data and so few members of the data team, tribal knowledge is a problem faced by most data teams.
Data requests are questions that employees have about data that exists in the organization or about new data isn't being collected yet. Traditionally, data teams will take data requests through an intake form or a Slack channel where employees can ask for the request.
We’re excited to introduce Secoda’s new (and most requested) feature, which brings one step close to getting everyone on the same page about data.
Everything you need to consider as you make your decision about building or buying your data discovery tools
We're extremely excited to announce our new feature in Secoda, which allows users to connect Secoda to Airflow.
We're extremely excited to announce our new feature in Secoda, which allows users to connect Secoda to dbt.
Solving data discovery starts by getting on top of your teams data debt.
Many companies have started to invest in their data analytics teams and processes to make their team more data-driven and self-sufficient.
How do different data experts think about the future of the modern data stack
As more startups collect data at an earlier stage, many companies are thinking about their analytics stack. Follow these steps to set up a modern data stack.
Small teams are collecting and storing more data than ever before.
As a new team in the data engineering space, we often stumble upon new tools in the industry that are solving some pressing problems.
A step by step guide to creating a data dictionary
Top 20 Most Commonly Used Data Engineering Tools 2023
A centralized, asynchronous, function agnostic data discovery tool can help all employees collaborate on data in a way that hasn’t been achieved by the existing tools.
Data discovery is going to change the way data-driven teams adopt data in the coming decade.
Secoda is the place to centralize company data. We’ve built Secoda as a single place for all incoming data and metadata, a single source of truth. The goal of Secoda is to help employees find and understand the right information as quickly as possible.