2024 Databricks Lakehouse Fundamentals Certification QUESTIONS WITH 100% SOLUTIONS LATEST UPDATE

Databricks - ANSWER A Software-As-A-Service company that makes big data and AI easier for organizations to manage, enabling data-driven innovation in all enterprises. Databricks Lakehouse Platform - ANSWER A platform that empowers everyone on a data science team to work together, in one secure platform, from the minute data is ingested into an organization through when it's cleaned up, analyzed, and used to inform business decisions. Lakehouse - ANSWER A storage technology that combines the most popular functionality from data warehouses and data lakes. An implementation uses similar data structures and data management features to those in a data warehouse, directly on the kind of low-cost storage used for data lakes. Data Warehouses - ANSWER A storage technology that generally follow a set of guidelines to design systems controlling the flow of data used in decision-making. They are designed to optimize data queries, prevent conflicts between concurrently running queries, support structured data, and make the assumption that data entered is unlikely to change with high frequency. Data Lakes - ANSWER A storage technology that allows an organization to permanently and cheaply store data of any nature in any format - in fact, data lakes allow both structured and semi-structured data to be stored alongside unstructured data like video, images, free text, and log files. Data Swamp - ANSWER A poorly maintained data lake that is difficult to navigate and query. Delta Lake - ANSWER An open-source storage layer that brings data reliability to data lakes through accuracy and completeness to the data. A part of the combination responsible for laying the foundation for the Lakehouse. ACID Transactions - ANSWER A reliability innovation for Delta Lake that guarantees data validity by performing changes to data as if they are a single operation. Indexing - ANSWER A performance innovation for Delta Lake that orders an unordered table to maximize the efficiency of queries. Table Access Control Lists (ACLs) - ANSWER A governance innovation for Delta Lake that ensures that only users who should have access to data can access it. Expectation-Setting - ANSWER A quality innovation for Delta Lake that configures based on your workload patterns and business needs. Bronze Layer - ANSWER A layer in the Delta Lake that contains raw data ingestion and history. Silver Layer - ANSWER A layer in the Delta Lake that contains filtered, cleaned, and augmented data. Gold Layer - ANSWER A layer in the Delta Lake that contains business-level aggregate data. Databricks SQL - ANSWER An interface to write queries that explore their organization's Delta Lake table. Regularly used code can be saved as snippets for quick reuse, and query results can be cached to keep the query short. Databricks Machine Learning - ANSWER An interface to explore data, prepare and process data, build and test machine learning models, deploy those models, and optimize them. Managed MLflow - ANSWER A component of Databricks Machine Learning that allows machine learning practitioners to easily access data about their models. Databricks Collaborative Notebooks - ANSWER A component of Databricks Machine Learning that is a web-based interface that contains runnable code, visualizations, and narrative text. They are used in data science and machine learning to perform exploratory data analysis and build machine learning models. They support multiple programming languages (SQL, Scala, R, Python, and Java), built-in data visualizations, automatic versioning, and the ability to automate processes. Databricks Machine Learning Runtime - ANSWER A component of Databricks Machine Learning that is a scalable computing resource that comes with built-in popular data science frameworks (interfaces that help data practitioners quickly build and deploy machine learning models). It provides an optimized computing environment for machine learning workflows. Feature Store - ANSWER A component of Databricks Machine Learning that provides data teams with the ability to streamline their work by creating new features to use in their machine learning models, exploring and reusing existing features, and building training data sets. AutoML - ANSWER A component of Databricks Machine Learning that fast tracks the machine learning workflow by providing training code for trial runs of models - data scientists can use this code to quickly assess the feasibility of using a data set for machine learning or to get a quick sanity check on the direction of an ML project. Model Serving - ANSWER A component of Databricks Machine Learning that provides a one-click deployment of any ML model as a REST endpoint for low latency serving. Integrates with the Model Registry to manage staging and production versions of endpoints. Customer-Managed VPC/VNET - ANSWER A private networks that can be deployed with custom network configurations to comply with internal cloud and data governance policies (as well as adhere to external regulations). Access Control Lists / IP Whitelisting - ANSWER A connection filtration mechanism that specify which connections can or cannot be made in and out of an organization's workspaces, minimizing the attack surface. Code Isolation - ANSWER A privacy feature that allows data practitioners can run their data analytics workflows on the same computational resources while ensuring each user only has access to the data they are authorized to access. Control Plane - ANSWER A collection of backend services that Databricks manages in its own cloud account.