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Azure Data Lake Analytics

Azure Data Lake Analytics

Overview

What is Azure Data Lake Analytics?

Microsoft's Azure Data Lake Analytics is a BI service for processing big data jobs without consideration for infrastructure.

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Recent Reviews

Value for Volume

8 out of 10
January 18, 2022
Incentivized
Used Azure Data Lake Analytics while working for a CPG major to store/process/analyze large volumes of data (daily cadence). Used Python …
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Awards

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Pricing

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Azure Data Lake Analytics

Azure Data Lake Analytics

N/A
Unavailable

What is Azure Data Lake Analytics?

Microsoft's Azure Data Lake Analytics is a BI service for processing big data jobs without consideration for infrastructure.

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Would you like us to let the vendor know that you want pricing?

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Product Details

What is Azure Data Lake Analytics?

Azure Data Lake Analytics Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(17)

Reviews

(1-1 of 1)
Companies can't remove reviews or game the system. Here's why
January 18, 2022

Value for Volume

Verified User
Program Manager in Information Technology
Management Consulting Company, 501-1000 employees
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Use Cases and Deployment Scope
Used Azure Data Lake Analytics while working for a CPG major to store/process/analyze large volumes of data (daily cadence). Used Python as a programming language for processing the stored data. Also, with fluctuating data volume across weekdays/weekends, ADL analytics was helpful in processing data on demand, and scale instantly, thereby enabling us to pay for the services used/rendered.
Pros and Cons
  • Effective and efficient data storage
  • pretty fast querying ability
  • Incredibly scalable (need based usage and billing)
  • There's a bit of bias towards cloud with ADL Analytics. Depending upon a company's infra strategy and investment plans, there are some challenges with migration and integeration.
  • Not worth the time/effort/money if the organization doesn't have "Volume" of data. Cost effective only when daily loads exceed around 1million.
  • While training materials are available online, Adoption rate - Yet to pick up.
Likelihood to Recommend
Azure Data Lake Analytics is best suited for -
1) Storing raw data ( original data format)
2) You can store Unstructured, semi-structured and structured in it
3) Data lake follows schema on the reading method in which data is transformed as per requirement basis

Not the best scenario when -

1) Data volume isn't great
2) Latency, and querying speed isn't the most important criteria

Most Important Features
  • Ability to store data in its native format (Unstructured, semi-structured, images, online reviews)
  • Scalable and flexible - according to data loads
  • Cheaper storage option
Return on Investment
  • Yet to realize its full potential - Owing to skill shortage in the org
  • Adoption across organization a challenge
Alternatives Considered
ADL Analytics supports big data such as Hadoop, HDInsight, Data lakes. Usually, a traditional data warehouse stores data from various data sources, transform data into a single format and analyze for decision making. Developers use complex queries that might take longer hours for data retrieval. With Data Lake Analytics, the processing is so smooth and fast that -- complex queries run within minutes, much to our surprise. Pretty amazing!
Other Software Used
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