Access modifiers, also known as access specifiers, determine the accessibility and scope of classes, methods, and other members. Scala's access modifiers closely resemble those of Java, although they provide more granular and powerful visibility control than Java.
Apache Airflow enables us to schedule tasks as code. In Airflow, a SLA determines the maximum completion time for a task or DAG. Note that SLAs are established based on the DAG execution date, not the task start time.
Amazon EMR is a managed cluster platform that makes it easier to run big data frameworks like Apache Hadoop and Apache Spark on AWS to process and analyze huge amounts of data.
Anti-patterns at first seem to be quick and reasonable, they typically have adverse effects in the future. They are design and code smells. It affects our software badly and adds technical debt. We should avoid them at all costs.
Apache Pinot is a real-time, distributed OLAP datastore that was built for low-latency, high-throughput analytics, making it perfect for user-facing analytical workloads. Pinot joins hands with Kafka and Presto to provide user-facing analytics.
Partitioning and bucketing are used to improve the reading of data by reducing the cost of shuffles, the need for serialization, and the amount of network traffic.
Caching is one of Spark's optimization strategies for reusing computations. It stores interim and partial results so they'll be utilised in subsequent computation stages.
Amazon EMR is a managed cluster platform that makes it easier to run big data frameworks like Apache Hadoop and Apache Spark on AWS to process and analyze huge amounts of data.
Data governance is the process of defining security guidelines and policies and making sure they are followed by having authority and control over how data assets are managed.
It's the process of designing and building systems for gathering vast quantities of raw operational data from a variety of sources and formats, analyzing, converting, and storing it at scale.
Partitioning and bucketing are used to improve the reading of data by reducing the cost of shuffles, the need for serialization, and the amount of network traffic.
Caching is one of Spark's optimization strategies for reusing computations. It stores interim and partial results so they'll be utilised in subsequent computation stages.
A data product is not the same as data as a product. A data product aids the accomplishment of the product's goal by using the data, whereas in data as a product, the data itself is seen as the actual product.
Caching is one of Spark's optimization strategies for reusing computations. It stores interim and partial results so they'll be utilised in subsequent computation stages.
A data product is not the same as data as a product. A data product aids the accomplishment of the product's goal by using the data, whereas in data as a product, the data itself is seen as the actual product.
Data governance is the process of defining security guidelines and policies and making sure they are followed by having authority and control over how data assets are managed.
It's the process of designing and building systems for gathering vast quantities of raw operational data from a variety of sources and formats, analyzing, converting, and storing it at scale.
When the granularity of data increases, its complexity also increases. At some point, we will reach a point where we cannot handle the volume of fresh data being generated.
Data governance is the process of defining security guidelines and policies and making sure they are followed by having authority and control over how data assets are managed.
Envelope encryption is a way of encrypting plaintext data using a key and then encrypting that key using an another key. This strategy is intended not just to make things more secure but also to enhance performance.
A data product is not the same as data as a product. A data product aids the accomplishment of the product's goal by using the data, whereas in data as a product, the data itself is seen as the actual product.
When the granularity of data increases, its complexity also increases. At some point, we will reach a point where we cannot handle the volume of fresh data being generated.
It's the process of designing and building systems for gathering vast quantities of raw operational data from a variety of sources and formats, analyzing, converting, and storing it at scale.
A data product is not the same as data as a product. A data product aids the accomplishment of the product's goal by using the data, whereas in data as a product, the data itself is seen as the actual product.
Envelope encryption is a way of encrypting plaintext data using a key and then encrypting that key using an another key. This strategy is intended not just to make things more secure but also to enhance performance.
Data governance is the process of defining security guidelines and policies and making sure they are followed by having authority and control over how data assets are managed.
Anti-patterns at first seem to be quick and reasonable, they typically have adverse effects in the future. They are design and code smells. It affects our software badly and adds technical debt. We should avoid them at all costs.
Envelope encryption is a way of encrypting plaintext data using a key and then encrypting that key using an another key. This strategy is intended not just to make things more secure but also to enhance performance.
Terraform is an open source infrastructure-as-code tool that allows us to programmatically provision the physical resources required for an application to run.
Terraform is an open source infrastructure-as-code tool that allows us to programmatically provision the physical resources required for an application to run.
Rust's ownership and borrowing features prevent us from experiencing memory-related problems. Rust is a great choice when performance matters and it solves pain points that bother many other languages.
Apache Pinot is a real-time, distributed OLAP datastore that was built for low-latency, high-throughput analytics, making it perfect for user-facing analytical workloads. Pinot joins hands with Kafka and Presto to provide user-facing analytics.
Apache Pinot is a real-time, distributed OLAP datastore that was built for low-latency, high-throughput analytics, making it perfect for user-facing analytical workloads. Pinot joins hands with Kafka and Presto to provide user-facing analytics.
Access modifiers, also known as access specifiers, determine the accessibility and scope of classes, methods, and other members. Scala's access modifiers closely resemble those of Java, although they provide more granular and powerful visibility control than Java.
Partitioning and bucketing are used to improve the reading of data by reducing the cost of shuffles, the need for serialization, and the amount of network traffic.
Apache Pinot is a real-time, distributed OLAP datastore that was built for low-latency, high-throughput analytics, making it perfect for user-facing analytical workloads. Pinot joins hands with Kafka and Presto to provide user-facing analytics.
Rust's ownership and borrowing features prevent us from experiencing memory-related problems. Rust is a great choice when performance matters and it solves pain points that bother many other languages.
Envelope encryption is a way of encrypting plaintext data using a key and then encrypting that key using an another key. This strategy is intended not just to make things more secure but also to enhance performance.
Rust's ownership and borrowing features prevent us from experiencing memory-related problems. Rust is a great choice when performance matters and it solves pain points that bother many other languages.
Access modifiers, also known as access specifiers, determine the accessibility and scope of classes, methods, and other members. Scala's access modifiers closely resemble those of Java, although they provide more granular and powerful visibility control than Java.
Apache Airflow enables us to schedule tasks as code. In Airflow, a SLA determines the maximum completion time for a task or DAG. Note that SLAs are established based on the DAG execution date, not the task start time.
Apache Airflow enables us to schedule tasks as code. In Airflow, a SLA determines the maximum completion time for a task or DAG. Note that SLAs are established based on the DAG execution date, not the task start time.
Terraform is an open source infrastructure-as-code tool that allows us to programmatically provision the physical resources required for an application to run.
Apache Airflow enables us to schedule tasks as code. In Airflow, a SLA determines the maximum completion time for a task or DAG. Note that SLAs are established based on the DAG execution date, not the task start time.
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