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There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.
The phData Toolkit continues to have additions made to it as we work with customers to accelerate their migrations , build a data governance practice , and ensure quality data products are built. This includes things like creating and modifying databases, schemas, and permissions. Let’s dive in and take a deeper look at these.
Over the last month, we’ve been heavily focused on adding additional support for SQL translations to our SQL Translations tool. Specifically, we’ve been introducing fixes and features for our Microsoft SQL Server to Snowflake translation. This is where the SQL Translation tool can be a massive accelerator for your migration.
You have tons of data and SQL to migrate, and you need to ensure that it’s done right, or it’s your job on the line! WIthin our Toolkit CLI, we primarily have two different tools: our SQL Translation Tool and our Data Source Tool. Added a default name (the folder or file name) when generating SQL reports.
It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively. Dolt Dolt is an open-source relational database system built on Git. Share features across the organization.
While many of our customers leverage our UI for tools like our SQL Translation or Privilege Audit tooling, there are limitations when it comes to using a UI. You wouldn’t want to pay someone (or perform yourself) to manually copy/paste each file into a browser window and copy/paste the translated SQL back.
Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. DataProfiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.
By maintaining clean and reliable data, businesses can avoid costly mistakes, enhance operational efficiency, and gain a competitive edge in their respective industries. Best Data Hygiene Tools & Software Trifacta Wrangler Pros: User-friendly interface with drag-and-drop functionality. Provides real-time data monitoring and alerts.
Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable. Perform dataprofiling (the process of examining, analyzing and creating summaries of datasets).
This is a difficult decision at the onset, as the volume of data is a factor of time and keeps varying with time, but an initial estimate can be quickly gauged by analyzing this aspect by running a pilot. Also, the industry best practices suggest performing a quick dataprofiling to understand the data growth.
It is known for its ability to connect to almost any database and offers features like reusable data flows, automating repetitive work. Trifacta Trifacta is a dataprofiling and wrangling tool that stands out with its rich features and ease of use.
Dataflows represent a cloud-based technology designed for data preparation and transformation purposes. Dataflows have different connectors to retrieve data, including databases, Excel files, APIs, and other similar sources, along with data manipulations that are performed using Online Power Query Editor.
Top Orchestration Tools for Snowflake Snowflake Snowflake has a native feature called tasks that can be used to schedule a single SQL statement, call a stored procedure or run procedural logic via Snowflake Scripting. Automate Data Quality Checks Integrate data quality checks and validations into your data pipelines.
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