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.
Fast and scalable azure data lake analytics!
Playing with data have never been easy with Azure Data Lake Analytic
Good choice regarding features
Value for Volume
Aggregate Data Lake Data
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Pricing
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?
Alternatives Pricing
What is Klipfolio?
Klipfolio PowerMetrics is a metric-centric business intelligence platform. Data teams are able to bring all of their data together and create a catalog of verified metrics that end users are able to explore and visualize using self-serve dashboards and reports.
What is Active Query Builder?
Active Query Builder is a component for business applications which helps users without any SQL experience to work with SQL queries and get data fast. Users can get a clear view of database schema and design SQL queries with natural point-and-click actions rather than tedious typing. Active Query…
Product Details
- About
- Tech Details
What is Azure Data Lake Analytics?
Azure Data Lake Analytics Technical Details
Operating Systems | Unspecified |
---|---|
Mobile Application | No |
Comparisons
Compare with
Reviews and Ratings
(17)Reviews
(1-6 of 6)- It combines big data.
- Monitors and alerts are helpful.
- Report visualization relies on analytics.
- It is compatible with Power BI services for report generation.
- The data pipeline is managed and monitored inefficiently.
- Streaming and event processing workloads are lacking.
- It's memory-intensive but useful for networking data and cloud storage.
Fast and scalable azure data lake analytics!
- Process large data transformation jobs using pretty much any language needed.
- Native integration with Azure storage.
- Top notch security that fulfills all audit needs.
- Easy to consolidate enterprise data under one location - Single source of truth.
- Learning curve and professional services were the only reason why we got up and running quickly - Not a downside but a need to know.
- Allows us to take in data, unstructured or structured
- Good documentation
- SaaS
- AWS Glue could be more effective.
- There is no 24/7 support.
- Documentation is not available online.
Good choice regarding features
- Easy usage
- Interface
- Connectivity
- Sometimes requires previous experience in cloud.
Value for Volume
- 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.
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
Aggregate Data Lake Data
- Reporting
- Data Aggregation
- Trends
- Pricing model, I understand why it is per jib but our junior engineers make mistakes.