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A Flexible and Efficient Storage System for Diverse Workloads

Cloudera

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 86
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Apache Spark vs MapReduce: A Detailed Comparison

Knowledge Hut

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. Also, Spark and MapReduce do complement each other on many occasions.

Hadoop 96
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Data Scientist Salary in India: Based on Location, Company, Experience

Knowledge Hut

The data goes through various stages, such as cleansing, processing, warehousing, and some other processes, before the data scientists start analyzing the data they have garnered. The data analysis stage is important as the data scientists extract value and knowledge from the processed, structured data.

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Five Strategies to Accelerate Data Product Development

Cloudera

From my discussions with Cloudera clients, data product development has been on top of the growth agenda in many industries such as Financial Services, Healthcare and Telecommunications. a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g.,

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What is Data Enrichment? Best Practices and Use Cases

Precisely

Determine what data you’ll need Once you’ve determined the use case, brainstorm and dig deeper into what your end goals are and what you need to know to get there. For example, will you need structured data, unstructured, or a combination?

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What is AWS Redshift? (Key Benefits & Limitations)

Edureka

Introduction Amazon Redshift, a cloud data warehouse service from Amazon Web Services (AWS), will directly query your structured and semi-structured data with SQL. Data warehousing: Modern companies have huge datasets, and if they could, they would put as much data as possible onto the Amazon Redshift.

AWS 40
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The Top 3 Data Mesh Challenges — and How to Solve Them

Ascend.io

If you work with data, you’ll have come across the term data mesh by now. This decentralized but interconnected approach to structuring data has become increasingly popular since the term was coined by Zhamak Dehghani 4 years ago.