share_log

Bigeye Launches Bigeye Dependency Driven Monitoring to Ensure Reliable Analytics

Bigeye Launches Bigeye Dependency Driven Monitoring to Ensure Reliable Analytics

Bigeye 推出 Bigeye 依赖驱动的监控功能,以确保可靠的分析
PR Newswire ·  03/25 11:15

SAN FRANCISCO, March 25, 2024 /PRNewswire/ -- Today Bigeye announces the availability of Bigeye Dependency Driven Monitoring. With this launch, Bigeye becomes the first data observability platform to allow enterprise data teams to connect their analytics dashboards, map every dependency across modern and legacy data sources, and deploy targeted data observability to ensure they stay reliable by default.

旧金山,2024年3月25日 /PRNewswire/ — Bigeye今天宣布推出Bigeye依赖驱动监控。此次发布后,Bigeye成为第一个允许企业数据团队连接分析仪表板、映射现代和传统数据源的所有依赖关系并部署有针对性的数据可观测性以确保它们在默认情况下保持可靠的数据可观测性平台。

According to Bigeye's 2023 State of Data Quality Report, 70% of business leaders don't trust analytics dashboards to make critical decisions due to regular data quality incidents.

根据Bigeye的《2023年数据质量状况报告》,由于定期发生数据质量事件,70%的企业领导者不信任分析仪表板来做出关键决策。

"Bigeye's new capabilities will let us surface the health of critical Power BI dashboards in real-time."

“Bigeye的新功能将使我们能够实时显示关键 Power BI 仪表板的运行状况。”

Post this
发布这个
Announcing Bigeye Dependency Driven Monitoring. Optimized data observability for every column powering critical analytics dashboards and data products.
宣布推出 Bigeye 依赖驱动型监控。优化了为关键分析仪表板和数据产品提供支持的每列的数据可观察性。

Regarding this challenge Kyle Kirwan, CEO and Co-founder of Bigeye, said, "We've spoken with hundreds of enterprise data leaders and, despite investing heavily in data quality tools and processes, they still struggle to deliver reliable data analytics to business users. Something the data observability industry hasn't yet solved is how to handle the complexity and size of large enterprise data pipelines. This is because enterprise dashboards have a long list of dependencies that span modern and legacy technologies and data observability platforms have yet to offer true support for the types of hybrid environments nearly all Fortune 500 companies have."

关于这一挑战,Bigeye首席执行官兼联合创始人凯尔·柯万表示:“我们已经与数百位企业数据领导者进行了交谈,尽管在数据质量工具和流程上进行了大量投资,但他们仍然难以为业务用户提供可靠的数据分析。数据可观测性行业尚未解决的问题是如何处理大型企业数据管道的复杂性和规模。这是因为企业仪表板有一长串的依赖关系,涵盖了现代和传统技术,而数据可观测性平台尚未为几乎所有《财富》500强公司都拥有的混合环境类型提供真正的支持。”

Bigeye Dependency Driven Monitoring uniquely solves this challenge by combining enterprise-grade lineage technology with data observability to automatically trace the entire enterprise data pipeline at column-level precision through traditional and modern technologies, ETL stages, and even across the boundary from cloud to on-premises environments.

Bigeye 依赖驱动监控通过将企业级世系技术与数据可观测性相结合,通过传统和现代技术、ETL 阶段,甚至跨越边界,从云到本地环境,以列级精度自动跟踪整个企业数据管道,从而独特地解决了这一挑战。

Bigeye Dependency Driven Monitoring improves data observability ROI

Bigeye 依赖驱动监控提高了数据可观察性 ROI

Without a clear understanding of which columns are critical dependencies for business operations and which are not, data engineering teams are left with no choice but to deploy broad, blanket monitoring across a large number of tables and columns to reach adequate coverage. While this approach helps engineers identify anomalies anywhere they occur in the data environment, it also requires them to manage higher compute costs, unwanted alert noise, and additional overhead as a result of deploying unnecessary monitoring.

如果不清楚哪些列是业务运营的关键依赖关系,哪些不是,数据工程团队别无选择,只能对大量表格和列进行广泛而全面的监控,以达到足够的覆盖范围。虽然这种方法可以帮助工程师识别数据环境中任何地方出现的异常,但它也要求他们管理更高的计算成本、不必要的警报噪音以及部署不必要的监控所产生的额外开销。

Bigeye Dependency Driven Monitoring turns this paradigm on its head by allowing data analysts and business users to start from their critical dashboard and—in just a few clicks—enable data observability on each column that matters, and none that don't.

Bigeye 依赖关系驱动监控颠覆了这种模式,它允许数据分析师和业务用户从他们的关键仪表板开始,只需点击几下,即可在每个重要的列上启用数据可观察性,而没有无关的列。

When compared with other data observability approaches, Bigeye Dependency Driven Monitoring provides:

与其他数据可观测性方法相比,Bigeye 依赖驱动监控提供:

  • Faster time to value and improved trust for data consumers.
  • Clear visibility into the health of the entire analytics data pipeline for analysts.
  • Reduced alert noise and faster issue resolution for data engineers.
  • Lower total cost of ownership and less compute overhead for data leaders.
  • 缩短价值实现时间,提高数据消费者的信任。
  • 让分析师清楚地了解整个分析数据管道的运行状况。
  • 减少了警报噪音,加快了数据工程师的问题解决速度。
  • 降低总拥有成本,减少数据领导者的计算开销。

When a data issue is detected, Bigeye will instantly notify each data source owner impacted through Slack or Microsoft Teams. Bigeye can also automatically create a bi-directional ticket in ITSM tools like JIRA and ServiceNow for integrated incident management.

当检测到数据问题时,Bigeye将立即通知每个受Slack或微软团队影响的数据源所有者。Bigeye还可以在JIRA和ServiceNow等ITSM工具中自动创建双向票证,以进行综合事件管理。

For data consumers, Bigeye will display data health updates directly in their analytics dashboard, providing instant insight into whether or not their analytics are reliable. Data engineering teams can then use Bigeye's lineage-powered root cause and impact analysis to quickly trace the data problem to the source for fast triage and resolution.

对于数据消费者,Bigeye将直接在其分析仪表板中显示数据运行状况更新,从而即时了解他们的分析是否可靠。然后,数据工程团队可以使用Bigeye的世系驱动的根本原因和影响分析,快速将数据问题追溯到源头,从而快速进行分类和解决。

Powered by Bigeye Lineage Plus—complete lineage for enterprise data stacks

由 Bigeye Lineage Plus 提供支持——企业数据堆栈的完整世系

Data lineage has become a ubiquitous feature for many types of data operations tools. Due to the complexity of mapping lineage in legacy or on-premises environments, most tools require the customer to use complex, custom APIs or manual entry to try and capture a full picture of an enterprise pipeline.

数据谱系已成为许多类型数据操作工具的无处不在的功能。由于在传统或本地环境中映射谱系的复杂性,大多数工具要求客户使用复杂的自定义 API 或手动输入来尝试捕捉企业管道的全貌。

Bigeye Dependency Driven Monitoring is powered by Bigeye Lineage Plus, a complete data lineage technology built to handle the largest, most complex enterprise pipelines. Bigeye Lineage Plus includes 50 connectors for transactional databases, cloud data warehouses, data lakes, ETL platforms, analytics tools, and more. Each connector includes parsers that trace lineage at the column level even as it moves from cloud to on-premises sources. As a result, data analysts and data engineers can view a single lineage map of their entire pipeline all the way through to an analytics dashboard or data product.

Bigeye 依赖关系驱动型监控由 Bigeye Lineage Plus 提供支持,这是一项完整的数据沿袭技术,专为处理最大、最复杂的企业管道而设计。Bigeye Lineage Plus 包括 50 个连接器,用于交易数据库、云数据仓库、数据湖、ETL 平台、分析工具等。每个连接器都包含解析器,即使从云端迁移到本地源代码时,也可以在列级别跟踪世系。因此,数据分析师和数据工程师可以查看其整个管道的单一谱系图,一直到分析仪表板或数据产品。

Bigeye Lineage Plus includes:

Bigeye Lineage Plus 包括:

  • 50+ connectors covering modern and legacy enterprise data sources
  • Support for cloud and on-premises infrastructure
  • ETL job information capture so no step in the pipeline is lost
  • 50 多个连接器,涵盖现代和传统企业数据源
  • 支持云和本地基础架构
  • 采集 ETL 任务信息,确保管道中的任何步骤都不会丢失

Bigeye Lineage Plus connectors for many of the most popular data sources are available today, including Tableau, Microsoft Power BI, Snowflake, Databricks, Google BigQuery, Amazon Redshift, Azure Synapse, IBM DB2, Oracle Database, MySQL, PostgreSQL, Microsoft SQL Server, SAP HANA, and Vertica.

当今许多最受欢迎的数据源的Bigeye Lineage Plus连接器上市,包括Tableau、微软 Power BI、Snowflake、Databricks、谷歌 BigQuery、亚马逊 Redshift、Azure Synapse、IBM DB2、甲骨文数据库、MySQL、PostgreSQL、微软 SQL Server、SAP HANA 和 Vertica。

A wide range of additional connectors will be made available throughout 2024, including Informatica PowerCenter, IBM Netezza, Teradata, SAS, Talend, SnapLogic, Apache Spark, IBM DataStage, MicroStrategy, QlikView, SAP Business Objects, Tibco Spotfire, and others.

2024年全年将提供各种其他连接器,包括Informatica PowerCenter、IBM Netezza、Teradata、SAS、Talend、SnapLogic、Apache Spark、IBM DataStage、微策略、QlikView、SAP业务对象、Tibco Spotfire等。

Customer quote: South32

客户报价:South32

"Bigeye's new capabilities will let us surface the health of critical Power BI dashboards in real-time to our data consumers who use them to make critical decisions daily in the field. Before Bigeye, we considered building this capability ourselves and we're confident that using Bigeye's pre-built Lineage Plus connectors will save us significant time and resources while speeding time-to-value."

“Bigeye的新功能将使我们能够向数据消费者实时显示关键的Power BI仪表板的运行状况,他们每天使用这些仪表板在现场做出关键决策。在使用Bigeye之前,我们曾考虑过自己建立这种能力,我们相信使用Bigeye的预建Lineage Plus连接器将为我们节省大量时间和资源,同时缩短价值实现时间。”

- Ash Smith, Manager, Data Platform, South32

-Ash Smith,数据平台经理,South32

About Bigeye

关于 Bigeye

Bigeye is enterprise-grade data observability for modern and legacy data stacks. Bigeye brings together data observability, end-to-end lineage, and scalability and security to give enterprise data teams unmatched insight into the reliability of data powering their business—no matter if it's on-prem, in the cloud, or hybrid.

Bigeye 是适用于现代和传统数据堆栈的企业级数据可观测性。Bigeye 将数据可观测性、端到端沿袭以及可扩展性和安全性相结合,为企业数据团队提供无与伦比的洞察力,了解数据为其业务提供动力的可靠性,无论是本地、云端还是混合环境。

SOURCE Bigeye

来源 Bigeye

声明:本内容仅用作提供资讯及教育之目的,不构成对任何特定投资或投资策略的推荐或认可。 更多信息
    抢沙发