DaaS平台

1. 产品介绍伴随着当前企业数据碎片化，业务数据存储在不同的数据系统中，对于数据的目录管理和数据的消费都带来了非常大的挑战。比如用户希望通过对业务的理解搜索或按业务目录查看相关数据，在获得数据后希望快速消费不同数据源的数据都存在很大的挑战。在当今大数据普遍应用的阶段，用户在高并发和大数据量获取和下载的过程中也经常会出现不同的性能和稳定性问题，所以企业急需一套完整的应用平台软件系统，能支持企业对不同数据源的数据业务目录管理、搜索、数据查询和API服务发布以及API服务行为分析的完整功能，提高企业对数据的全生命周期管理，同时高效稳定提供用户对数据的消费能力，完整实现数据即服务（Data As a Service）的消费理念，让数据发挥对业务的更好服务。麦聪数据即服务平台主要根据企业业务用户在数据使用中的痛点和关注点，打造一个端到端的从数据的搜索、数据的理解、数据的查看和数据消费等闭环的数据流程，帮助企业级用户更开放地、更好地完成对数据的管理和使用。2. DaaS平台的特点- 开箱即用：安装简便，提供绿色安装版;- 部署模式：支持预置与云部署模式;- 易用：界面简洁，无需培训，同时适用业务人员;- 支持所有主流数据库：MySQL,Oracle,PostgreSQL,Hadoop,Hive等;- 低TCO：无需再单独购置ETL工具;- 全文检索：Google式搜索快速找到所需数据;- 100%自开发国产软件：满足某些企业对国产化的要求;- 安全性高：权限管理贯穿整个平台;- 集成性强：同一平台上原生的各个模块，天生无排斥性集成，可以一站式进行数据发现、抓取、全文搜索、查看样本、下载、关注、数据众包与标签管理;- API服务自主发布：支持IT、业务部门自主发布数据服务;- 用户的数据行为分析：帮助为IT更好的管理数据资产;- 数据超市：业务用户自助式的使用数据API产品.3. 应用场景3.1 提高企业数据资产管理能力：数据资产化管理和运营一直是大中企业、集团型企业客户数字化转型的重要工作，很多企业在经历数年的数据建设后，对数据的运营管理和使用变得越来越重要。在实际工作中，自开发报表，大屏，资产使用大屏和数据服务对外等已经成为数据工作的重要。过去比较常见的构建方式都是基于不同数据源抽取到一个平台进行统一消费或者针对单独系统开发API对接报表系统。这样的方式工作量会比较大，同时有可能无法让运营部门实时看到最新的数据。通过DaaS平台的数据资产化和数据服务化能力可以满足企业客户的这一实际需求，部署DaaS平台后无缝集成企业客户所需的主流厂商数据平台，低代码自动生成数据服务API，分钟级别完成开发，实时查看最新的业务数据，全局权限管理，事前申请事后日志追踪，通过平台化思维可以有效提升企业客户的数字化管理能力和服务水平。3.2 加速企业数字化服务转型：为了支持业务高速增长和数字化转型，很多企业已经构建了比较完善且高效的数据平台系统。系统环境相对也比较复杂，可能会包含各种关系数据库，Hadoop大数据平台，数据中台等多种不同的数据平台系统。各业务系统包含供应商管理系统、客户管理系统等经常需要从数据平台获取业务数据，比如发票查询，服务订单查询等。部署DaaS平台后，开发团队针对各个业务需求和所需取数的平台不再需要人工单独开发接口，只需一分钟即可生成一个数据服务API接口，高效稳定支持用户高频次访问和使用。有效避免了开发效率和数据传输稳定性等外界因素的干扰，每次新的需求或前后台出现变化，不再需要重新开发耗时费力，同时还可以统一管理和监控接口，可以有效加速企业客户的数字化转型效率。3.3 让企业用户实现数据自助服务很多企业在长期的数字化建设后，构建了相对完善且复杂的数字化系统架构。其中可能会包括本地部署和私有云、公有云等混合云架构的数据库。数据库类型包含目前市面上占有率较高的Oracle数据库、微软的MSSQL和IBM、MySQL的数据平台，及Hadoop集群。部署DaaS平台，可以极大提升企业员工的开发和运营效率，将员工从繁重又重复的工作中解放出来，让员工更高效的专注在实际的业务中而不是数据的传输。不再需要员工人工开发数据后导出、校验、审核再传输到相应业务平台上，通过简单设置可直接生成数据下载任务，将原来以天为单位的工作量变成分钟级，极大提高了企业员工自助化数据服务的能力。

1. Product Introduction: With the current fragmentation of enterprise data, where business data is stored across disparate data systems, significant challenges arise for both data catalog management and data consumption.
For example, users face major hurdles when attempting to search for relevant data based on business context or browse via business catalogs, as well as when trying to quickly consume data from multiple data sources after acquiring it.
Furthermore, in the current era of widespread big data adoption, users often encounter performance and stability issues during high-concurrency, large-volume data acquisition and download processes.
Thus, enterprises urgently need a comprehensive application platform software system that supports full functions including business catalog management, search, data query, API service publishing, and API service behavior analysis for data from diverse data sources. This system will enhance enterprises' full-lifecycle data management capabilities, provide users with efficient and stable data consumption capabilities, fully realize the Data As a Service (DaaS) consumption concept, and enable data to better serve business operations.
The Maicong Data As a Service Platform is developed based on the pain points and concerns of enterprise business users during data usage, creating an end-to-end closed-loop data workflow covering data search, data understanding, data preview, and data consumption, to help enterprise users manage and utilize data more openly and effectively.

2. Features of the DaaS Platform
- Out-of-the-box: Easy to install, with a portable (green) installation package available;
- Deployment Modes: Supports both on-premises and cloud deployment;
- User-friendly: Simple interface, no specialized training required, suitable for business personnel;
- Compatibility with All Major Databases: Supports MySQL, Oracle, PostgreSQL, Hadoop, Hive, and other mainstream databases;
- Low Total Cost of Ownership (TCO): No need to purchase separate ETL tools;
- Full-text Search: Google-like search enables quick locating of required data;
- 100% Independently Developed Domestic Software: Meets the localization requirements of certain enterprises;
- High Security: Permission management runs through the entire platform;
- Strong Integration: Native modules on the same platform are inherently compatible without integration conflicts, enabling one-stop operations including data discovery, crawling, full-text search, sample preview, download, following, data crowdsourcing, and tag management;
- Autonomous API Service Publishing: Enables IT and business departments to independently publish data services;
- User Data Behavior Analysis: Assists IT teams in better managing data assets;
- Data Marketplace: Allows business users to self-service access data API products.

3. Application Scenarios
3.1 Enhancing Enterprise Data Asset Management Capabilities
Data asset-based management and operation have always been critical tasks for large, medium-sized, and group enterprise customers during their digital transformation. After years of data infrastructure construction, many enterprises find that data operation, management, and utilization are becoming increasingly important. In practical work, self-developed reports, large screens, asset usage dashboards, and external data services have become core components of data work. Previously, common construction methods involved extracting data from different sources into a unified platform for centralized consumption, or developing API-connected report systems for individual systems. Such approaches require substantial workloads, and may fail to allow operation departments to access real-time latest data. The data assetization and data service capabilities of the DaaS platform can meet the actual needs of enterprise customers. After deploying the DaaS platform, enterprises can seamlessly integrate mainstream vendor data platforms required, generate data service APIs with low-code automation, complete development within minutes, view real-time latest business data, implement global permission management, pre-use application and post-operation log tracing. With a platform-based mindset, this can effectively improve the digital management capabilities and service levels of enterprise customers.

3.2 Accelerating Enterprise Digital Service Transformation
To support rapid business growth and digital transformation, many enterprises have built relatively mature and efficient data platform systems with complex environments, which may include various relational databases, Hadoop big data platforms, data middle platforms, and other different data platform systems. Various business systems, such as supplier management systems and customer management systems, often need to obtain business data from data platforms, such as invoice query and service order query. After deploying the DaaS platform, development teams no longer need to manually develop interfaces for individual business requirements and data extraction platforms. Instead, they can generate a data service API interface in just one minute, efficiently and stably supporting high-frequency user access and usage. This effectively avoids interference from external factors such as development efficiency and data transmission stability. When new requirements arise or front-end and back-end changes occur, there is no need to re-develop time-consuming and labor-intensive solutions. Additionally, the platform enables unified management and monitoring of interfaces, effectively accelerating the digital transformation efficiency of enterprise customers.

3.3 Enabling Enterprise Users to Achieve Self-service Data Utilization
After years of digital construction, many enterprises have built relatively mature and complex digital system architectures, which may include databases deployed in on-premises environments, private clouds, public clouds, and other hybrid cloud architectures. Database types include high-market-share Oracle databases, Microsoft MSSQL, IBM, MySQL data platforms, and Hadoop clusters. Deploying the DaaS platform can greatly improve the development and operation efficiency of enterprise employees, freeing them from heavy and repetitive work, allowing them to focus more on actual business operations rather than data transmission. Employees no longer need to manually develop data, export, verify, audit, and then transmit the data to corresponding business platforms. Instead, they can directly generate data download tasks through simple configuration, turning workloads that originally took days into minute-level operations, greatly improving the self-service data service capabilities of enterprise employees.

搜集汇总

背景与挑战

背景概述

DaaS平台是一个企业级数据统一管理和服务平台，支持多种主流数据库和部署模式，提供数据资产管理、API服务发布及用户行为分析等功能，旨在提升企业数据管理效率和数字化服务能力。该平台适用于数据资产化运营、加速企业数字化转型及实现用户数据自助服务等场景。