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At the beginning of this series, we wondered why tools like ChatGPT are not yet widely used in production, and the answer lay in the lack of availability and accessibility of data.
However, data alone does not create value. Value is created only when data is used to answer specific questions. For example: Are quality variations attributable to the new raw material? Has the energy-saving measure shown an effect? Was production this month better or worse than last month? Can errors be detected early?
ENLYZE also offers features to answer such questions with data. But industrial processes are diverse and complex, and not all questions can be answered with the same solutions. Additionally, there are team preferences or company-wide policies to consider. This may include expertise in Power BI or the requirement to develop applications only within the Azure Cloud. Therefore, an important aspect of the IIoT platform from ENLYZE is that it provides data to other systems via simple and standardized interfaces – openness instead of closed systems, working more with the data instead of for the data.
But what tools are available? How do they differ, and which is best suited for your specific problem? We have analyzed and compared the most common data visualization tools. Most use cases can be implemented with one of the following three functions or a combination thereof:
Representation of time series,
Representation of key figures (KPIs),
Sending alerts/messages.
As a fourth comparison criterion, we considered the difficulty of installation. This is subjective and depends on individual familiarity with the technology and the specific environment in which it is used. And the best part: All mentioned tools are compatible with the ENLYZE IIoT platform and can be used for data analysis.
If you have little time for a complete analysis in text form, you will find a tabular overview at the end of this blog post.
Overview Blog Series Connectivity & Machine Data:
Digitalization Dilemma: Working for the data or working with the data
No more closed systems
Ready for all challenges in production with ENLYZE and Grafana
Grafana
Grafana is an open-source platform for real-time monitoring and visualization of metrics from various data sources. It is ideal for large amounts of time-series data and allows for quick creation and sharing of dashboards. It also has capabilities for visualizing KPIs, but is not as feature-rich as some other tools.
Alerts can be set up via the "Alert" feature and can be sent by email, Microsoft Teams, and Slack, among others. The complete list can be found here. The installation is moderately complex and a large number of data sources can be integrated.
Kibana
Kibana is part of the Elastic (ELK) Stack and specializes in time-series data. It is particularly well-suited for log and event data. Visualizing KPIs is possible, but not as intuitive or powerful as in others. Alert functions can be implemented with "Watcher" or "Alerting" and notifications via email, Slack, and webhooks are supported. Setup is moderate to complex, as it requires setting up and maintaining Elasticsearch, Logstash, and Kibana.
Tableau
Tableau is known for its strong KPI visualization capabilities. However, time series are not Tableau's focus and are only supported to a moderate extent. Most alerts require manual setup and are not a core competency of Tableau. Messages via email and Slack are supported. The user interface is very intuitive and user-friendly. The installation effort is moderate to complex, especially for on-premise installations.
Power BI
Power BI is a business analytics tool from Microsoft that can also visualize time-series data. However, the focus is on visualizing KPIs. It offers real-time notifications of data changes, but only emails or notifications within the Power BI app (Microsoft ecosystem) are supported. Installation is straightforward, and dashboards can be well integrated into Microsoft products.
Google Looker Studio
Google Looker Studio (formerly Data Studio) is a business intelligence tool within the Google Cloud Platform and is comparable to Power BI. Similar to Tableau and Power BI, time-series data is supported but is not the focus. Alerts can be set for email or Slack but require some manual effort. Since it is completely web-based, installation is straightforward. However, connecting data sources requires some knowledge of the Google Cloud Platform.
Azure TimeSeries Insights
Azure TimeSeries Insights is specifically designed for time-series data and is therefore excellent for examining time-series data. However, the representation of KPIs is not the focus and is therefore poorly supported. Alert functions are not present but can be implemented via Azure Logic Apps or Azure Monitor. Installation is moderately to labor-intensive and data integration requires an Azure event source such as IoT Hub or Event Hub.
Datadog
Datadog is primarily a tool for monitoring cloud applications and servers but can also be used as a monitoring and analysis platform for machine data. Visualizing KPIs is possible but is not the main focus. The alert functionality is very well developed. Datadog offers real-time alerts and can be integrated with various communication platforms such as Slack, PagerDuty, etc. Installation is moderately complex and data can be transmitted via agents, APIs, or libraries.
Compatibility with ENLYZE
All mentioned tools are compatible with the ENLYZE platform. Other tools can also be integrated, provided they support the data interfaces. If a direct integration via the API is not possible, custom connectors can be developed, or we can assist with the integration.
Are you wondering if ENLYZE can be combined with your data visualization tool? Just write to us at hello@enlyze.com and let us know which tool you are using. We will then check compatibility.
Grafana is particularly popular with our customers. Therefore, we simplified the integration and developed a dedicated data source for Grafana. This can be installed as a plug-in with one click. All you need afterward is your own API key to create dashboards with your machine data.
In the next blog post, we will present a complete use case with the combination of ENLYZE and Grafana. Just click on the next blog post in the overview below:
Overview of the Blog Series on Connectivity & Machine Data:
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