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Python for Data Engineering

Ascend.io

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

It eliminates the cost and complexity around data preparation, performance tuning and operations, helping to accelerate the movement from batch to real-time analytics. The latest Rockset release, SQL-based rollups, has made real-time analytics on streaming data a lot more affordable and accessible.

SQL 52
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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

Options for joining data in MongoDB include denormalization or use of the $lookup operator , but both are less flexible and powerful than a relational join. 2 – Use a Data Virtualization Tool The next approach is to use a data virtualization tool. The benefit of these tools is that they’re built specifically for data analytics.

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14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

They highlight competence in data management, a pivotal requirement in today's business landscape, making certified individuals a sought-after asset for employers aiming to efficiently handle, safeguard, and optimize data operations. Skills acquired : Core data concepts. The role that is covered by this certification is DBA.

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Data Aggregation: Definition, Process, Tools, and Examples

Knowledge Hut

If you would like to learn more about different data aggregation techniques check out a Data Engineer certification program. What is Data Aggregation? The process of merging and summarizing data from various sources in order to generate insightful conclusions is known as data aggregation.

Process 59
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DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

Rockset

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available. While this can work, there is a better way.

SQL 52
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The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

What if we told you that one of the world’s most powerful search and analytics engines started with the humble goal of organizing a culinary enthusiast’s growing list of recipes? To help her, Banon developed a search engine for her recipe collection. But like any technology, it has its share of pros and cons.