Precision Marketing

Information from multiple channels needs to be combined for associative analysis to improve the conversion rate. 

Advantages

• Cross-source analysis

  When advertisement CTR data is stored in OBS and user registration data in RDS, you can query and analyze it directly. There is no need to migrate it to DLI.

• Pure SQL

  With multiple data sources interconnected, you can map them together by creating a table using just SQL statements.

Log Analysis

Running a gaming company calls for a quality data analysis platform to improve ad placements, improve new player retention, improve operations, and get better feedback for future game iterations.  

PainPoints

Log analysis is usually performed by period. During the idle periods between each task, resources are wasted.

Advantages

• Pay-per-use billing

  Reduce costs by more than 50% compared with purchasing exclusive clusters. We only bill you for the resources actually used for scheduling.

• Converged analysis

  You only need a single copy of metadata for real-time cleaning, offline ETL processing, and interactive analysis. You can directly use the data processing result for data mining.

Log Analysis

If you run a large enterprise, different departments in the company may need to manage resources independently. You need fine-grained permissions management for data security and improved management efficiency.  

Advantages

• Fine-grained permission management

  Grant permissions by column or by specific operations, such as insert and overwrite; and control read and write permissions for the metadata.

• Unified management

  Use a single IAM account to manage the multiple employees in your company.

Gene Data Management

Third-party analysis libraries based on the Spark distributed framework, such as ADAM and Hail, are necessary for genome analysis.

Pain Points

High technical skills are required to install analysis libraries such as ADAM and Hail.

Every time you create a cluster, you have to install these analysis libraries again.

Advantages

• Custom images

  You can package third-party analysis libraries, like ADAM and Hail, into custom images and upload them directly to the Software Repository for Container (SWR). When using DLI, custom images in SWR are automatically pulled.

• Built-in base images

  Huawei enhanced Spark and Flink images in multiple versions and open-source AI images (Tensorflow/Keras/PyTorch) are built in to DLI for your convenience.

Real-time Risk Control

Almost every aspect of financial services involves some sort of risk control. A comprehensive system is required.

Pain Points

There is very little tolerance for excessive latency when it comes to risk control.

Advantages

• High throughput/Low latency

  You can perform real-time data analysis in DLI with the help of an Apache Flink dataflow model. A single CPU can process 1,000 to 20,000 messages per second.

• Cloud ecosystem

  You can save real-time data streams to multiple cloud services such as CloudTable and SMN.

Real-time Large Screen

With epidemics like COVID-19 raging across the globe, governments need to be able to monitor key data in real-time on a large screen display, so they can scientifically manage epidemic control.

Pain Points

Government employees do not necessarily have a background in big data. SQL is usually far more familiar.

Advantages

• Query within milliseconds

  Based on the powerful in-memory computing framework, the built-in openLooKeng engine optimizes query performance to achieve interactive analysis in milliseconds.

• Easy to use

  You only need SQL syntax for DLI queries. The syntax is fully compatible with standard ANSI SQL 2003.

Geographic Big Data Analysis

Geographic big data can involve massive volumes of data, for example petabytes of satellite imaging data. It also includes many different types of data. There is, for example, structured remote sensing image raster data, vector data, unstructured spatial location data, and 3D modeling data. An efficient mining tool is a must for geographic data analysis.

Advantages

• Spatial data analysis operators

  Spark spatial data analysis algorithm operators in DLI enable real-time stream processing and offline batch processing. You can import massive data types, including structured remote sensing image data, unstructured 3D modeling, and laser point cloud data in DLI.

• CEP SQL

  SQL statements are all that is needed for yaw detection and geo-fencing.

• Big data processing

  You can quickly migrate terabytes,or even exabytes, of remote sensing images to the cloud and slice the images to data sources for distributed batch processing.