What is Tableau and what are its top alternatives?
Top Alternatives to Tableau
DOMODomo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform. ...
SplunkIt provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...
LookerWe've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way. ...
QlikViewIt is a business discovery platform that provides self-service BI for all business users in organizations. With this tool, you can analyze data and use your data discoveries to support decision making. ...
Qlik SenseIt helps uncover insights that query-based BI tools simply miss. Our one-of-a-kind Associative Engine brings together all your data so users can freely search and explore to find new connections. AI and cognitive capabilities offer insight suggestions, automation and conversational interaction. ...
Power BIIt aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. ...
SisenseIt is making business intelligence (BI) analytics easy with its simple drag-and-drop and scalable end-to-end BI processes that help to prepare, analyze, and visualize multiple complex datasets quickly. ...
QlikTurn your data into business value faster with Qlik, the only end-to-end data integration and data analytics solutions for modern business intelligence. ...
Tableau alternatives & related posts
DOMO
related DOMO posts
- Ability to style search results into reports2
- Alert system based on custom query results2
- API for searching logs, running reports2
- Query engine supports joining, aggregation, stats, etc2
- Query any log as key-value pairs1
- Splunk language supports string, date manip, math, etc1
- Granular scheduling and time window support1
- Custom log parsing as well as automatic parsing1
- Dashboarding on any log contents1
- Rich GUI for searching live logs1
- Splunk query language rich so lots to learn1
related Splunk posts
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
We are currently exploring Elasticsearch and Splunk for our centralized logging solution. I need some feedback about these two tools. We expect our logs in the range of upwards > of 10TB of logging data.
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
- Price3
related Looker posts
We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.
related QlikView posts
related Qlik Sense posts
- Cross-filtering17
- Powerful Calculation Engine2
- Access from anywhere2
- Intuitive and complete internal ETL2
- Database visualisation2
- Azure Based Service1
related Power BI posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
Which among the two, Kyvos and Azure Analysis Services, should be used to build a Semantic Layer?
I have to build a Semantic Layer for the data warehouse platform and use Power BI for visualisation and the data lies in the Azure Managed Instance. I need to analyse the two platforms and find which suits best for the same.
related Sisense posts