Sisense is a business intelligence and data visualization software that helps organizations make 'sense' of complex data by providing powerful analytics and reporting capabilities.
It can connect to a wide variety of data sources and allows users to create interactive dashboards, charts, and reports to gain insights from their data. Sisense also offers advanced features such as real-time data visualization, machine learning, and natural language processing capabilities.
It is aimed to help data analysts, data engineers, and other business users to quickly and easily gain insights from their data.
Sisense is primarily used as BI platform and data visualization tool.
Business intelligence (BI) is the process of converting raw data into meaningful information that can be used to make business decisions. Sisense is designed to help organizations make sense of complex data by providing powerful analytics and reporting capabilities.
With Sisense, users can connect to a wide variety of data sources and create interactive dashboards, charts, and reports to gain insights from their data. The software enables users to:
Create and share interactive dashboards and reports
Perform advanced analytics and data exploration
Drill down into data to understand the underlying causes of trends or issues
Monitor key performance indicators (KPIs) in real-time
Create alerts when certain conditions are met
Collaborate with team members and share insights
Enrich data with machine learning, natural language processing, and geospatial analysis.
Sisense is used across various industries and departments, including finance, healthcare, retail, manufacturing, and logistics, to name a few. It is used by business analysts, data scientists, and other users who need to quickly and easily manipulate data.
Yes, Sisense is a data visualization tool. Data visualization is the process of converting raw data into graphical representations, such as charts and graphs, to make the data more understandable and meaningful. Sisense API provides a wide range of visualization options, including bar charts, line charts, scatter plots, heat maps, and many more metrics.
Users can create interactive dashboards and reports that allow them to explore the data in different ways, making it easy to gain insights and identify patterns.
Additionally, users can customize the visualizations to match their specific needs and preferences. Sisense also includes real-time data visualization capabilities, which allows users to monitor key performance indicators (KPIs) and get alerts when certain conditions are met.
Sisense offers cloud-based deployment options. Cloud-based deployment means that the software and its associated data are hosted on remote servers and accessed over the internet, rather than being installed on local servers or workstations. This deployment model allows users to access their data and analytics from anywhere with an internet connection.
With Sisense cloud-based deployment options, customers have the flexibility to choose between a fully-managed SaaS (Software as a Service) offering, where Sisense manages the infrastructure, deployment, and maintenance, or a hybrid deployment, while customers can leverage the benefits of both on-premise and cloud deployments.
In addition to the cloud-based deployment options, Sisense also offers on-premises deployment, where the software is installed on the customer's own servers. This allows customers to store their data locally and have full control over their own infrastructure.
Sisense uses its proprietary in-chip technology to handle Sisense data storage and processing. The In-Chip technology allows Sisense to compress and index the data on the fly, and store it in a columnar format, which makes the data retrieval and analysis extremely fast.
Sisense supports a wide variety of data sources, including traditional relational databases, such as MySQL, SQL Server, Oracle, and PostgreSQL, as well as big data sources, such as Amazon Redshift, Google BigQuery, and Apache Hadoop.
Additionally, Sisense also supports NoSQL databases, such as MongoDB, Cassandra, and Elasticsearch, as well as cloud-based data sources, such as Salesforce, Google Analytics, and others.
Sisense's ability to connect to various data pipelines, combined with its in-chip technology, allows users to easily combine and analyze data from multiple sources in a single platform, which gives them a more complete picture of their business. This helps users to make better and more informed decisions.
Sisense includes some ETL (Extract, Transform, Load) capabilities, but it is not a traditional ETL tool.
ETL tools are primarily used to extract data from various sources, transform the data into a format that can be used for analysis, and then load the data into a data warehouse or other data store for reporting and analysis.
Sisense can connect to a wide variety of data sources and allows users to combine and analyze data from multiple sources in a single platform. However, Sisense is not designed to be a full-featured ETL tool and its main focus is on data visualization and analytics, rather than data integration and transformation.
It is recommended to use Sisense in conjunction with a traditional ETL tool to perform the data integration and transformation tasks and then use Sisense to perform the data analysis and visualization tasks.
This approach allows users to take advantage of the strengths of each tool, and to have a complete data management and analysis solution.
Sisense ElastiCube is a proprietary data modeling technology developed by Sisense. It is a columnar, in-memory data store that is optimized for fast data retrieval and analysis of workflows.
The most common use case of ElastiCube includes store and process data for use in Sisense's business intelligence and data visualization software.
The ElastiCube technology allows Sisense BI tool to handle large amounts of data quickly and efficiently. It compresses and indexes data on the fly, and stores it in a columnar format which makes the data retrieval and analysis extremely fast.
ElastiCube also allows users to perform advanced analytics, such as data blending, data mapping, and data modeling. Data blending allows users to combine data from multiple sources, while data mapping allows users to clean and shape the data sets before it is loaded into the system. Data modeling allows users to create a semantic layer on top of the data, which makes it easier to create and understand the relationships between the data.
Sisense ElastiCube is a columnar, in-memory data store that is optimized for fast data retrieval and analysis, it is used by Sisense software to handle data storage, data processing, and data modeling, allowing users to perform advanced analytics, data visualization and gain insights from their data.
Sisense Live Modeling is a feature of the Sisense business intelligence and data analytics platform that allows users to perform real-time data modeling and analysis without the need for data warehousing or ETL processes.
It is used as data connector which allows users to connect to various data sources and perform live modeling and analysis on the data, providing real-time insights and enabling users to make data-driven decisions.
A dedicated ETL (Extract, Transform, Load) tool should be used when you need to perform complex data transformations or when you need to perform data integration between multiple systems.
These tools are designed to handle large volumes of data and provide a wide range of error-free data manipulation and integration capabilities.
Examples of popular dedicated ETL tools are:
It is no-code ETL / ELT tool best suited for data integration.
Informatica is a portfolio of high-performance data virtualization tools which also includes data governance, integration services and analytics features.
Talend is a platform with no-code options for data transformation and ETL.
Dell Boomi is a low-code tool that works on public clouds, private clouds, and on-premise deployments.
Jitterbit is an integration platform-as-a-service (iPaaS) for SaaS and on-premise applications.
SnapLogic is a no code data integration solution that uses artificial intelligence to create automations.
Integrate.io is a data integration platform that supports ETL and ELT workflows.
Oracle has a suite of tools for data integration, including Oracle Data Integrator and Oracle GoldenGate.
Pentaho is a platform provides a range of tools for data operations.
Hevo is a data replication and ETL tool for near real-time data processes.
IRI Voracity is an ETL tool that handles data sets cleansing for structured, semi-structured, or unstructured formats.
SAP is a suite of tools including SAP Data Integrator, SAP Cloud Platform, and more.
ZigiOps is a data integration service to streamline data workflows across different types of data. It offers no-code features and real-time data integration.
Microsoft has several data services in its suite of tools, including Azure Logic Apps, Microsoft Flow, and SQL Server Integration Services (SSIS). These are best for companies with deep integrations other tools in the Microsoft ecosystem (Office: Excel, Word, Access, Outlook).
IBM has data tool chain, including InfoSphere DataStage and App Connect.