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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

It becomes prohibitively complex and expensive to use a data warehouse to serve real-time analytics. Rockset: Real-time Analytics Built for the Cloud Rockset is doing for real-time analytics what Snowflake did for batch. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.

SQL 52
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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

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Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources. A data lake stores current and historical data similar to a data warehouse. Gen 2 Azure Data Lake Storage . Cloud storage provided by Google .

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Cloud composer and PubSub outputs are Apache Beam and connected to Google Dataflow.

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100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. E.g. PostgreSQL, MySQL, Oracle, Microsoft SQL Server.

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The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59
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Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. All updates are appended rather than written over existing data records. Companies also started appending additional related time-stamped data to existing datasets, a process called data enrichment.