Alibaba Cloud DataWorks Highly Recognized by Forrester

Analyses in this article are based on Now Tech: Cloud Data Warehouse, Q1 2018 (Published by Noel Yuhanna, March 13, 2018). The views and opinions expressed herein are those of the author.

On March 13, 2018, Forrester issued the <b>Now Tech: Cloud Data Warehouse Q1 2018</b> report. In this report, Forrester comprehensively assessed Cloud Data Warehouses (CDWs) in aspects such as main features, regional performance, market segmentation, and customers.

In this report, Forrester highlighted four core CDW features:

<b>Flexible deployment</b>

CDWs are expected to have several flexible deployment modes. For small enterprises, CDWs should provide the online multi-tenant mode to allow these customers to quickly mobilize computing resources and implement data warehouse deployment in just several minutes. For medium and large enterprises, CDWs should support the exclusive or local deployment mode to provide robust computing performance and absolute security as well as leave out technical details of high complexity

<b>Efficient data migration to cloud</b>

For customers that have not yet migrated their data warehouses to cloud or customers that adopt online and offline hybrid architectures, CDWs should provide a fast and low-cost approach to help users implement data collection.

<b>Diverse analysis methods </b>

CDWs should support multiple technical means to help users get desired data processing capabilities in various business scenarios.

<b>Excellent security</b>

CDWs should provide security in various aspects, including data encryption, auditing, data desensitization and access control.

Before analyzing DataWorks, we will first take a quick look at its role in the Alibaba Cloud CDW service system and its product architecture.

<b>Data integration</b>: Integrate heterogeneous data to collect numerous data from various source systems on big data cloud platforms

<b>Data development</b>: Data warehouse design and ETL development

<b>O&amp;M monitoring</b>: O&amp;M monitoring over jobs in the ETL process

<b>Real-time analytics</b>: Real-time data exploration and analysis

<b>Data asset management</b>: Metadata management, data map, data lineage, data asset graph, etc.

<b>Data quality</b>: The system for data quality control, monitoring, verification and assessment

<b>Data security</b>: data permission management, classified data marking, data desensitization and data audits

<b>Data service</b>: data sharing, data switching and data API services

It is obvious that efficient data integration methods can significantly facilitate the migration of enterprise data to cloud. During the initial migration stage, enterprises need to quickly and securely migrate their data assets to cloud; during the stage of continuous business operations, enterprises need to input various kinds of data into CDWs and then output processed data from CDWs to individual business units.

<b>Multi-tenant isolation</b>

<b>Data security level setting</b>

Data security levels allow users to discover and locate sensitive data, and see the sensitive data distribution on data resource platforms. Auto-discover sensitive data based on specified insensitive data types and classify insensitive data. Appropriate security rules are applied based on secret levels such as Top Secret, Confidential and General.

<b>Data access audit </b>

<b>Data desensitization</b>

With "Internet Plus" further applied in different industries, there is an increasing need for enterprises to manage, process and employ their data assets. Internet companies can quickly use their big data processing capability to meet other enterprises' needs. That also explains why these four cloud service providers, instead of long-established data warehouse companies like Oracle and IBM, are listed in the Forrester report as first-tier CDW providers.