Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use.
With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.
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Trifacta
Trifacta offers an efficient solution for preparing data and constructing data pipelines in the cloud. By leveraging visual and intelligent assistance, it enables users to expedite data preparation, leading to quicker insights. Data analytics projects can falter due to poor data quality; therefore, Trifacta equips you with the tools to comprehend and refine your data swiftly and accurately. It empowers users to harness the full potential of their data without the need for coding expertise. Traditional manual data preparation methods can be tedious and lack scalability, but with Trifacta, you can create, implement, and maintain self-service data pipelines in mere minutes instead of months, revolutionizing your data workflow. This ensures that your analytics projects are not only successful but also sustainable over time.
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Tableau Prep
Tableau Prep revolutionizes traditional data preparation within organizations by offering an intuitive visual interface for data merging, shaping, and cleansing, enabling analysts and business users to initiate their analysis more swiftly. It consists of two key products: Tableau Prep Builder, designed for creating data flows, and Tableau Prep Conductor, which facilitates the scheduling, monitoring, and management of those flows throughout the organization. Users can leverage three different views to examine row-level details, column profiles, and the overall data preparation workflow, allowing them to choose the most appropriate view based on their specific tasks. Editing a value is as simple as selecting it and making changes directly, while modifications to join types yield immediate results, ensuring real-time feedback even with extensive datasets. Every action taken allows for instant visualization of data changes, regardless of the volume, and Tableau Prep Builder empowers users to reorder steps and experiment freely without risk. This flexibility fosters a more dynamic data preparation process, encouraging innovation and efficiency in data handling.
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