{"sectionGroup":{"sections":null},"DashboardExample":{"display_title_text":"IOT Live Energy Dashboard","display_title_icon":false,"dashboard_icon":false,"show_on_category_page":false,"category_page_summary":"IoT data visualization is becoming an industry-standard almost across the board. IoT analytics allows users to check on their devices and react quickly to incoming data. Embedding IoT data streams into a Sisense dashboard is a great way to close the loop on monitoring your IoT devices and promptly running analytics on the same data.","solution_page_title":"","solutions_page_summary":"","cloud_trial_dashboard_id":"5d9264c51d3cb956980f336c","dashboard_screenshot":false,"has_implementation_kit":true,"technical_content":"

Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n

Objectives<\/h3>\n
\n
Analyze device behavior to find inefficiencies<\/li>\n
See which devices are unstable<\/li>\n
Stop devices if unexpected energy consumption is detected<\/li>\n<\/ul>\n
KPIs Architecture<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n
\n
Objectives<\/p>\n<\/td>\n
\n
KPIs<\/p>\n<\/td>\n
\n
Measures<\/p>\n<\/td>\n
\n
Data Source<\/p>\n<\/td>\n<\/tr>\n
\n
Analyze device behavior to find inefficiencies<\/p>\n<\/td>\n
\n
Total Energy Consumption<\/strong><\/p>\n<\/td>\n
\n
sum([Power])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n
\n
IOT Energy<\/p>\n<\/td>\n<\/tr>\n
\n
avg Current<\/strong><\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Voltage<\/strong><\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Frequency<\/strong><\/p>\n<\/td>\n
\n
avg([Frequency])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
See which devices are unstable<\/p>\n<\/td>\n
\n
Average Power<\/p>\n<\/td>\n
\n
avg([Power])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Current<\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Voltage<\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Stop devices if unexpected energy consumption is detected<\/p>\n
<\/p>\n<\/td>\n
\n
BloX Webhook to device<\/p>\n<\/td>\n
\n
N\/A<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Plugins & Scripts<\/h3>\n
\n
Sisense BloX<\/a><\/li>\n
Percent Complete Circle and Indicator<\/a><\/li>\n
Stream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\n
Display BloX Widgets Horizontally<\/a><\/li>\n
Widget Title Style Plugin<\/a><\/li>\n<\/ol>\n","implementation_kit_download":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/IoT-Energy.zip","documentation_link":"https:\/\/documentation.sisense.com\/latest\/content\/verticals.htm","kpi":false,"dashboard_example_categories":[{"category":false},{"category":false},{"category":{"isSticky":false,"id":25722,"title":"Manufacturing","uri":"\/dashboard-examples\/manufacturing\/","content":"","excerpt":"Track the metrics that matter to your manufacturing department.","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png"}}}}],"dashboard_roles":"C-level Executive, VP Operations, Directors, Line Manager","connector":[{"connector":{"isSticky":false,"id":16757,"title":"Amazon Redshift","uri":"\/data-connector\/redshift\/","content":"\r\n
Optimize Your Cloud Investments with Sisense and Redshift<\/h2>\r\n\r\n\r\n
Sisense offers a native data connector to Amazon Redshift, a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. Store data in Redshift database<\/a> and query this data in Sisense to optimize performance, improve cost control and deliver greater ease of use.<\/p>\r\n\r\n\r\n
As well, Sisense provides the ability to prepare, govern, analyze and mashup data<\/a> from multiple sources. The powerful In-Chip\u00ae engine unifies decentralized data and balances workloads. Use Sisense to optimize your investment in the cloud and build faster, more flexible analytical apps with reduced management overhead and cost.<\/p>\r\n\r\n\r\n
In addition to Redshift, Sisense has data connectors to Kinesis<\/a> Data Firehose, SageMaker, EMR, Glue, DynamoDB, Athena, and many more out of the box. With Sisense, the benefits of Amazon Web Services empower more builders and analysts at every step of the BI workflow.\u00a0<\/p>\r\n
$\"\"$ <\/p>\r\n\r\n\r\n
Benefits of Amazon Redshift<\/h2>\r\n\r\n\r\n
Integrating your Redshift data warehouse<\/a> with Sisense\u2019s toolkit presents several noteworthy benefits including:<\/p>\r\n\r\n\r\n
\r\n\t
Best for frequent queries, real-time queries using columnar storage, complex data aggregations, already an AWS customer<\/li>\r\n\t
If currently running on AWS, Redshift should be your first choice. \u00a0Redshift integrates with a variety of AWS services such as Kinesis Data Firehose, SageMaker, EMR, Glue, DynamoDB, Athena, Database Migration Service (DMS), Schema Conversion Tools (SCT), CloudWatch, etc.<\/li>\r\n\t
In Redshift you are given control over how to tune your big data database<\/a>. Enables you to tweak the data model and fine tune the cluster for the best performance and lowest infrastructure cost<\/li>\r\n\t
Fastest for real-time queries using columnar storage<\/li>\r\n<\/ul>\r\n\r\n\r\n
Amazon Redshift introduces RA3 nodes with managed storage enabling independent compute and storage scaling<\/strong><\/p>\r\n\r\n\r\n
Amazon Redshift RA3 nodes with managed storage are generally available and enable you to scale and pay for compute and storage independently, allowing you to size your cluster based only on your compute needs. Now you can analyze even more data cost-effectively.<\/p>\r\n\r\n\r\n
RA3 nodes are built on the AWS Nitro System and feature high bandwidth networking and performance indistinguishable from bare metal. RA3 nodes use very large, high performance SSDs as local caches. RA3 nodes leverage your workload patterns and advanced data management techniques, such as automatic fine-grained data eviction and intelligent data pre-fetching, to deliver the performance of local SSD while scaling storage automatically to S3. RA3 nodes remain fully compatible with all your existing workloads.<\/p>\r\n\r\n\r\n
To get started with RA3 nodes see the\u00a0cluster management guide<\/a>. You can find more information on pricing by visiting the\u00a0 Amazon Redshift pricing<\/a>\u00a0page.<\/p>\r\n\r\n\r\n
Benefits of Sisense and Amazon Redshift<\/h2>\r\n\r\n\r\n
Instant Insights with Native Connection to Redshift<\/strong><\/p>\r\n\r\n\r\n
The Sisense live connection uses Amazon Redshift to power queries and dashboards in real time<\/a>. Connect and create relationships to quickly prepare complex live data models for any purpose. Run live analysis on any dataset to make well-supported decisions on the spot.<\/p>\r\n\r\n\r\n
Hybrid Architecture to Integrate Data from Redshift and Other Data Sources<\/strong>
\r\nBeyond live analysis, Sisense delivers easy-to-use analytics that seamlessly blends live data from Redshift and other data sources to make more informed decisions. Sisense\u2019s high-performance In-Chip\u00ae engine and Elastic Data Hub analyze other data alongside real-time queries from Redshift. Whether you want to a connect a multi-cloud environment, combine data that\u2019s not yet in Redshift, or keep pace with rapidly changing requirements, Sisense provides a hybrid solution to manage, prepare, combine, and analyze distributed data.<\/p>\r\n\r\n\r\n
A True Single Version of the Truth<\/strong>
\r\nPerennial growth in data often leaves data sources outside of Redshift. Sisense eradicates these data silos by providing a single data analytics software<\/a> for all data models and sources. Teams and departments can easily create multiple high-performance data models in the Sisene Elastic Data Hub that can be analyzed alongside live data from Redshift. This increases the adoption of Redshift and also brings all data into a unified governed platform reducing management overhead.<\/p>\r\n\r\n\r\n
Quickly Migrate to the Cloud<\/strong>
\r\nSisense enables you to connect and analyze data before and during your migration to Redshift. Native data models can be used to enable analysis and after migration; taking seconds to redirect any analysis to query live data in Redshift. This provides business continuity and enables you to get value from data instantly without waiting for a lengthy migration process.<\/p>\r\n\r\n\r\n
Remove Bottlenecks for Ultimate Service Flexibility<\/strong>
\r\nSisense ease of use matched with Redshift allows anybody to model and analyze complex data. Business users don\u2019t need to seek technical assistance every time they want to query live data connections. Offer the right service model based on user needs and skills to provide analytics on demand.<\/p>\r\n\r\n\r\n
Balance Complex Workloads for Operational Excellence<\/strong>
\r\nShift data exploration and analysis to Elastic Data Models to optimize performance and lower TCO. Sisense\u2019s In-Chip\u00ae engine gives you a time-saving, cost-efficient way to cache existing data. Instead of refreshing the whole database every time you add something new, query cached data for historical insights and connect live to Redshift for more timely questions.<\/p>\r\n\r\n\r\n
Integrate Further with Managed Cloud BI<\/strong>
\r\nFocus on what matters and Sisense managed Cloud. With Sisense Managed Cloud, you don't need to worry about hardware or IT. Get Sisense fully-managed, secure, and scalable cloud service.<\/p>\r\n\r\n\r\n
\r\n\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the Redshift Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/aws-redshift-connector.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/aws-redshift-connector.png"}}}},{"connector":{"isSticky":false,"id":29417,"title":"Snowflake","uri":"\/data-connector\/snowflake\/","content":"\r\n
Sisense connects directly to the Snowflake data warehouse using a connector officially certified by Snowflake to deliver an optimized customer experience, flexibly delivering access to all of your present and future data for detailed data exploration and insights. Sisense\u2019s Elastic Data Engine provides the flexibility to prepare, query and manage data within Snowflake using both code and a web-based, visual data modeling experience.<\/p>\r\n\r\n\r\n
Organizations can harness the power and elasticity of Snowflake by using Sisense\u2019s advanced data pipelines, SQL-based materialized views and live data models to power complex ad-hoc analysis, dashboards and analytic apps.<\/p>\r\n\r\n\r\n
Snowflake & Sisense\u2019s Elastic Data Engine Features:<\/p>\r\n\r\n\r\n
\r\n\t
Securely connect and ingest data into Snowflake to create a single store for your data using SQL, Python and R<\/li>\r\n\t
Explore both modeled and raw data to easily answer complex and ambiguous business questions without having to rebuild any upfront models<\/li>\r\n\t
Optimize raw data stored in Snowflake with materialized views that further powers self-service analytics and query performance from Snowflake\u00a0<\/li>\r\n\t
Connect, prepare and combine together dozens of tables directly in Snowflake into a single live model that can be accessed, queried and reused by all users across multiple dashboards<\/li>\r\n\t
Mashup data into a cached data model from Snowflake with other data that has not, or can not be migrated, to Snowflake due to data ownership, regulatory or other concerns\u00a0<\/li>\r\n<\/ul>\r\n\r\n\r\n
Sisense enables organizations to integrate with Snowflake\u2019s existing systems of record and authentication systems to ensure users have adaptive governance to support the distribution of data to any organizational policy. Multi-level security from a system, object, role, and row-level that can be programmatically automated ensures to ensure organizations can quickly scale the integration between Snowflake + Sisense.\u00a0<\/p>\r\n\r\n\r\n
<\/p>\r\n\r\n\r\n
\r\n
\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the Snowflake Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/snowflake1.jpg","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/snowflake1.jpg"}}}},{"connector":{"isSticky":false,"id":16812,"title":"Google BigQuery","uri":"\/data-connector\/google-bigquery\/","content":"\r\n
Sisense connects directly to the BigQuery data warehouse to flexibly deliver access to all of your present and future data for detailed data exploration and insights. Sisense\u2019s Elastic Data Engine provides the flexibility to prepare, query and manage data within BigQuery using both code and a web-based, visual data modeling experience.\u00a0<\/p>\r\n\r\n\r\n
Organizations can harness the power and elasticity of BigQuery by using Sisense\u2019s advanced data pipelines, SQL-based materialized views and live data models to power complex ad-hoc analysis, dashboards and analytic apps.<\/p>\r\n\r\n\r\n
BigQuery & Sisense\u2019s Elastic Data Engine Features:<\/p>\r\n\r\n\r\n
\r\n\t
Securely connect and ingest data into BigQuery to create a single store for your data using SQL, Python and R<\/li>\r\n\t
Explore both modeled and raw data to easily answer complex and ambiguous business questions without having to rebuild any upfront models<\/li>\r\n\t
Optimize raw data stored in BigQuery with materialized views that further powers self-service analytics and query performance from BigQuery<\/li>\r\n\t
Connect, prepare and combine together dozens of tables directly in BigQuery into a single live model that can be accessed, queried and reused by all users across multiple dashboards<\/li>\r\n\t
Mashup data into a cached data model from BigQuery with other data that has not, or can not be migrated, to BigQuery due to data ownership, regulatory or other concerns\u00a0<\/li>\r\n<\/ul>\r\n\r\n\r\n
Sisense enables organizations to integrate with BigQuery existing systems of record and authentication systems to ensure users have adaptive governance to support the distribution of data to any organizational policy. Multi-level security from a system, object, role, and row-level that can be programmatically automated ensures to ensure organizations can quickly scale the integration between BigQuery + Sisense.\u00a0<\/p>\r\n\r\n\r\n
<\/p>\r\n\r\n\r\n
\r\n
\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the BigQuery Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/logo-connector-google-big-query1.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/logo-connector-google-big-query1.png"}}}}],"kpis_without_links":"Total Energy Consumption, avg Current, avg Voltage, avg Frequency, Average Power, BloX Webhook to device"},"MarketplaceApp":{"technical_content":"
Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n
Objectives<\/h3>\n
\n
Analyze device behavior to find inefficiencies<\/li>\n
See which devices are unstable<\/li>\n
Stop devices if unexpected energy consumption is detected<\/li>\n<\/ul>\n
KPIs Architecture<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n
\n
Objectives<\/p>\n<\/td>\n
\n
KPIs<\/p>\n<\/td>\n
\n
Measures<\/p>\n<\/td>\n
\n
Data Source<\/p>\n<\/td>\n<\/tr>\n
\n
Analyze device behavior to find inefficiencies<\/p>\n<\/td>\n
\n
Total Energy Consumption<\/strong><\/p>\n<\/td>\n
\n
sum([Power])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n
\n
IOT Energy<\/p>\n<\/td>\n<\/tr>\n
\n
avg Current<\/strong><\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Voltage<\/strong><\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Frequency<\/strong><\/p>\n<\/td>\n
\n
avg([Frequency])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
See which devices are unstable<\/p>\n<\/td>\n
\n
Average Power<\/p>\n<\/td>\n
\n
avg([Power])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Current<\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Voltage<\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Stop devices if unexpected energy consumption is detected<\/p>\n
<\/p>\n<\/td>\n
\n
BloX Webhook to device<\/p>\n<\/td>\n
\n
N\/A<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Plugins & Scripts<\/h3>\n
\n
Sisense BloX<\/a><\/li>\n
Percent Complete Circle and Indicator<\/a><\/li>\n
Stream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\n
Display BloX Widgets Horizontally<\/a><\/li>\n
Widget Title Style Plugin<\/a><\/li>\n<\/ol>\n"},"dashboardExample":{"kpi":false,"dashboard_example_categories":[{"category":false},{"category":false},{"category":{"isSticky":false,"id":25722,"title":"Manufacturing","uri":"\/dashboard-examples\/manufacturing\/","content":"","excerpt":"Track the metrics that matter to your manufacturing department.","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png"}}}}],"connector":[{"connector":{"isSticky":false,"id":16757,"title":"Amazon Redshift","uri":"\/data-connector\/redshift\/","content":"\r\n
Optimize Your Cloud Investments with Sisense and Redshift<\/h2>\r\n\r\n\r\n
Sisense offers a native data connector to Amazon Redshift, a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. Store data in Redshift database<\/a> and query this data in Sisense to optimize performance, improve cost control and deliver greater ease of use.<\/p>\r\n\r\n\r\n
As well, Sisense provides the ability to prepare, govern, analyze and mashup data<\/a> from multiple sources. The powerful In-Chip\u00ae engine unifies decentralized data and balances workloads. Use Sisense to optimize your investment in the cloud and build faster, more flexible analytical apps with reduced management overhead and cost.<\/p>\r\n\r\n\r\n
In addition to Redshift, Sisense has data connectors to Kinesis<\/a> Data Firehose, SageMaker, EMR, Glue, DynamoDB, Athena, and many more out of the box. With Sisense, the benefits of Amazon Web Services empower more builders and analysts at every step of the BI workflow.\u00a0<\/p>\r\n
$\"\"$ <\/p>\r\n\r\n\r\n
Benefits of Amazon Redshift<\/h2>\r\n\r\n\r\n
Integrating your Redshift data warehouse<\/a> with Sisense\u2019s toolkit presents several noteworthy benefits including:<\/p>\r\n\r\n\r\n
\r\n\t
Best for frequent queries, real-time queries using columnar storage, complex data aggregations, already an AWS customer<\/li>\r\n\t
If currently running on AWS, Redshift should be your first choice. \u00a0Redshift integrates with a variety of AWS services such as Kinesis Data Firehose, SageMaker, EMR, Glue, DynamoDB, Athena, Database Migration Service (DMS), Schema Conversion Tools (SCT), CloudWatch, etc.<\/li>\r\n\t
In Redshift you are given control over how to tune your big data database<\/a>. Enables you to tweak the data model and fine tune the cluster for the best performance and lowest infrastructure cost<\/li>\r\n\t
Fastest for real-time queries using columnar storage<\/li>\r\n<\/ul>\r\n\r\n\r\n
Amazon Redshift introduces RA3 nodes with managed storage enabling independent compute and storage scaling<\/strong><\/p>\r\n\r\n\r\n
Amazon Redshift RA3 nodes with managed storage are generally available and enable you to scale and pay for compute and storage independently, allowing you to size your cluster based only on your compute needs. Now you can analyze even more data cost-effectively.<\/p>\r\n\r\n\r\n
RA3 nodes are built on the AWS Nitro System and feature high bandwidth networking and performance indistinguishable from bare metal. RA3 nodes use very large, high performance SSDs as local caches. RA3 nodes leverage your workload patterns and advanced data management techniques, such as automatic fine-grained data eviction and intelligent data pre-fetching, to deliver the performance of local SSD while scaling storage automatically to S3. RA3 nodes remain fully compatible with all your existing workloads.<\/p>\r\n\r\n\r\n
To get started with RA3 nodes see the\u00a0cluster management guide<\/a>. You can find more information on pricing by visiting the\u00a0 Amazon Redshift pricing<\/a>\u00a0page.<\/p>\r\n\r\n\r\n
Benefits of Sisense and Amazon Redshift<\/h2>\r\n\r\n\r\n
Instant Insights with Native Connection to Redshift<\/strong><\/p>\r\n\r\n\r\n
The Sisense live connection uses Amazon Redshift to power queries and dashboards in real time<\/a>. Connect and create relationships to quickly prepare complex live data models for any purpose. Run live analysis on any dataset to make well-supported decisions on the spot.<\/p>\r\n\r\n\r\n
Hybrid Architecture to Integrate Data from Redshift and Other Data Sources<\/strong>
\r\nBeyond live analysis, Sisense delivers easy-to-use analytics that seamlessly blends live data from Redshift and other data sources to make more informed decisions. Sisense\u2019s high-performance In-Chip\u00ae engine and Elastic Data Hub analyze other data alongside real-time queries from Redshift. Whether you want to a connect a multi-cloud environment, combine data that\u2019s not yet in Redshift, or keep pace with rapidly changing requirements, Sisense provides a hybrid solution to manage, prepare, combine, and analyze distributed data.<\/p>\r\n\r\n\r\n
A True Single Version of the Truth<\/strong>
\r\nPerennial growth in data often leaves data sources outside of Redshift. Sisense eradicates these data silos by providing a single data analytics software<\/a> for all data models and sources. Teams and departments can easily create multiple high-performance data models in the Sisene Elastic Data Hub that can be analyzed alongside live data from Redshift. This increases the adoption of Redshift and also brings all data into a unified governed platform reducing management overhead.<\/p>\r\n\r\n\r\n
Quickly Migrate to the Cloud<\/strong>
\r\nSisense enables you to connect and analyze data before and during your migration to Redshift. Native data models can be used to enable analysis and after migration; taking seconds to redirect any analysis to query live data in Redshift. This provides business continuity and enables you to get value from data instantly without waiting for a lengthy migration process.<\/p>\r\n\r\n\r\n
Remove Bottlenecks for Ultimate Service Flexibility<\/strong>
\r\nSisense ease of use matched with Redshift allows anybody to model and analyze complex data. Business users don\u2019t need to seek technical assistance every time they want to query live data connections. Offer the right service model based on user needs and skills to provide analytics on demand.<\/p>\r\n\r\n\r\n
Balance Complex Workloads for Operational Excellence<\/strong>
\r\nShift data exploration and analysis to Elastic Data Models to optimize performance and lower TCO. Sisense\u2019s In-Chip\u00ae engine gives you a time-saving, cost-efficient way to cache existing data. Instead of refreshing the whole database every time you add something new, query cached data for historical insights and connect live to Redshift for more timely questions.<\/p>\r\n\r\n\r\n
Integrate Further with Managed Cloud BI<\/strong>
\r\nFocus on what matters and Sisense managed Cloud. With Sisense Managed Cloud, you don't need to worry about hardware or IT. Get Sisense fully-managed, secure, and scalable cloud service.<\/p>\r\n\r\n\r\n
\r\n\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the Redshift Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/aws-redshift-connector.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/aws-redshift-connector.png"}}}},{"connector":{"isSticky":false,"id":29417,"title":"Snowflake","uri":"\/data-connector\/snowflake\/","content":"\r\n
Sisense connects directly to the Snowflake data warehouse using a connector officially certified by Snowflake to deliver an optimized customer experience, flexibly delivering access to all of your present and future data for detailed data exploration and insights. Sisense\u2019s Elastic Data Engine provides the flexibility to prepare, query and manage data within Snowflake using both code and a web-based, visual data modeling experience.<\/p>\r\n\r\n\r\n
Organizations can harness the power and elasticity of Snowflake by using Sisense\u2019s advanced data pipelines, SQL-based materialized views and live data models to power complex ad-hoc analysis, dashboards and analytic apps.<\/p>\r\n\r\n\r\n
Snowflake & Sisense\u2019s Elastic Data Engine Features:<\/p>\r\n\r\n\r\n
\r\n\t
Securely connect and ingest data into Snowflake to create a single store for your data using SQL, Python and R<\/li>\r\n\t
Explore both modeled and raw data to easily answer complex and ambiguous business questions without having to rebuild any upfront models<\/li>\r\n\t
Optimize raw data stored in Snowflake with materialized views that further powers self-service analytics and query performance from Snowflake\u00a0<\/li>\r\n\t
Connect, prepare and combine together dozens of tables directly in Snowflake into a single live model that can be accessed, queried and reused by all users across multiple dashboards<\/li>\r\n\t
Mashup data into a cached data model from Snowflake with other data that has not, or can not be migrated, to Snowflake due to data ownership, regulatory or other concerns\u00a0<\/li>\r\n<\/ul>\r\n\r\n\r\n
Sisense enables organizations to integrate with Snowflake\u2019s existing systems of record and authentication systems to ensure users have adaptive governance to support the distribution of data to any organizational policy. Multi-level security from a system, object, role, and row-level that can be programmatically automated ensures to ensure organizations can quickly scale the integration between Snowflake + Sisense.\u00a0<\/p>\r\n\r\n\r\n
<\/p>\r\n\r\n\r\n
\r\n
\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the Snowflake Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/snowflake1.jpg","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/snowflake1.jpg"}}}},{"connector":{"isSticky":false,"id":16812,"title":"Google BigQuery","uri":"\/data-connector\/google-bigquery\/","content":"\r\n
Sisense connects directly to the BigQuery data warehouse to flexibly deliver access to all of your present and future data for detailed data exploration and insights. Sisense\u2019s Elastic Data Engine provides the flexibility to prepare, query and manage data within BigQuery using both code and a web-based, visual data modeling experience.\u00a0<\/p>\r\n\r\n\r\n
Organizations can harness the power and elasticity of BigQuery by using Sisense\u2019s advanced data pipelines, SQL-based materialized views and live data models to power complex ad-hoc analysis, dashboards and analytic apps.<\/p>\r\n\r\n\r\n
BigQuery & Sisense\u2019s Elastic Data Engine Features:<\/p>\r\n\r\n\r\n
\r\n\t
Securely connect and ingest data into BigQuery to create a single store for your data using SQL, Python and R<\/li>\r\n\t
Explore both modeled and raw data to easily answer complex and ambiguous business questions without having to rebuild any upfront models<\/li>\r\n\t
Optimize raw data stored in BigQuery with materialized views that further powers self-service analytics and query performance from BigQuery<\/li>\r\n\t
Connect, prepare and combine together dozens of tables directly in BigQuery into a single live model that can be accessed, queried and reused by all users across multiple dashboards<\/li>\r\n\t
Mashup data into a cached data model from BigQuery with other data that has not, or can not be migrated, to BigQuery due to data ownership, regulatory or other concerns\u00a0<\/li>\r\n<\/ul>\r\n\r\n\r\n
Sisense enables organizations to integrate with BigQuery existing systems of record and authentication systems to ensure users have adaptive governance to support the distribution of data to any organizational policy. Multi-level security from a system, object, role, and row-level that can be programmatically automated ensures to ensure organizations can quickly scale the integration between BigQuery + Sisense.\u00a0<\/p>\r\n\r\n\r\n
<\/p>\r\n\r\n\r\n
\r\n
\r\n
\r\n
\r\n
Getting Started<\/h2>\r\n
To start using the BigQuery Connector, simply follow the instructions here<\/a>.<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n","excerpt":"","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/logo-connector-google-big-query1.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/logo-connector-google-big-query1.png"}}}}],"displayTitleText":"IOT Live Energy Dashboard","displayTitleIcon":false,"dashboardIcon":false,"showOnCategoryPage":false,"categoryPageSummary":"IoT data visualization is becoming an industry-standard almost across the board. IoT analytics allows users to check on their devices and react quickly to incoming data. Embedding IoT data streams into a Sisense dashboard is a great way to close the loop on monitoring your IoT devices and promptly running analytics on the same data.","solutionPageTitle":"","solutionsPageSummary":"","cloudTrialDashboardId":"5d9264c51d3cb956980f336c","dashboardScreenshot":false,"hasImplementationKit":true,"technicalContent":"
Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n
Objectives<\/h3>\n
\n
Analyze device behavior to find inefficiencies<\/li>\n
See which devices are unstable<\/li>\n
Stop devices if unexpected energy consumption is detected<\/li>\n<\/ul>\n
KPIs Architecture<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n
\n
Objectives<\/p>\n<\/td>\n
\n
KPIs<\/p>\n<\/td>\n
\n
Measures<\/p>\n<\/td>\n
\n
Data Source<\/p>\n<\/td>\n<\/tr>\n
\n
Analyze device behavior to find inefficiencies<\/p>\n<\/td>\n
\n
Total Energy Consumption<\/strong><\/p>\n<\/td>\n
\n
sum([Power])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n
\n
IOT Energy<\/p>\n<\/td>\n<\/tr>\n
\n
avg Current<\/strong><\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Voltage<\/strong><\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Frequency<\/strong><\/p>\n<\/td>\n
\n
avg([Frequency])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
See which devices are unstable<\/p>\n<\/td>\n
\n
Average Power<\/p>\n<\/td>\n
\n
avg([Power])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Current<\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Voltage<\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Stop devices if unexpected energy consumption is detected<\/p>\n
<\/p>\n<\/td>\n
\n
BloX Webhook to device<\/p>\n<\/td>\n
\n
N\/A<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Plugins & Scripts<\/h3>\n
\n
Sisense BloX<\/a><\/li>\n
Percent Complete Circle and Indicator<\/a><\/li>\n
Stream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\n
Display BloX Widgets Horizontally<\/a><\/li>\n
Widget Title Style Plugin<\/a><\/li>\n<\/ol>\n","implementationKitDownload":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/IoT-Energy.zip","documentationLink":"https:\/\/documentation.sisense.com\/latest\/content\/verticals.htm","dashboardExampleCategories":[{"category":false},{"category":false},{"category":{"isSticky":false,"id":25722,"title":"Manufacturing","uri":"\/dashboard-examples\/manufacturing\/","content":"","excerpt":"Track the metrics that matter to your manufacturing department.","tags":false,"categories":{"edges":[]},"author":{"node":{"firstName":"Sisense","lastName":"Team","avatar":{"url":""}}},"featuredImage":{"node":{"sourceUrl":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png","guid":"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Manufacturing-Dashboard-Hero-Visual-1.png"}}}}],"dashboardRoles":"C-level Executive, VP Operations, Directors, Line Manager","kpisWithoutLinks":"Total Energy Consumption, avg Current, avg Voltage, avg Frequency, Average Power, BloX Webhook to device"},"marketplaceApp":{"technicalContent":"
Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n
Objectives<\/h3>\n
\n
Analyze device behavior to find inefficiencies<\/li>\n
See which devices are unstable<\/li>\n
Stop devices if unexpected energy consumption is detected<\/li>\n<\/ul>\n
KPIs Architecture<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n
\n
Objectives<\/p>\n<\/td>\n
\n
KPIs<\/p>\n<\/td>\n
\n
Measures<\/p>\n<\/td>\n
\n
Data Source<\/p>\n<\/td>\n<\/tr>\n
\n
Analyze device behavior to find inefficiencies<\/p>\n<\/td>\n
\n
Total Energy Consumption<\/strong><\/p>\n<\/td>\n
\n
sum([Power])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n
\n
IOT Energy<\/p>\n<\/td>\n<\/tr>\n
\n
avg Current<\/strong><\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Voltage<\/strong><\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
avg Frequency<\/strong><\/p>\n<\/td>\n
\n
avg([Frequency])<\/p>\n
Dimensions:<\/p>\n
device<\/p>\n<\/td>\n<\/tr>\n
\n
See which devices are unstable<\/p>\n<\/td>\n
\n
Average Power<\/p>\n<\/td>\n
\n
avg([Power])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Current<\/p>\n<\/td>\n
\n
avg([Current])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Average Voltage<\/p>\n<\/td>\n
\n
avg([Voltage])<\/p>\n
Dimensions:<\/p>\n
date, device<\/p>\n<\/td>\n<\/tr>\n
\n
Stop devices if unexpected energy consumption is detected<\/p>\n
<\/p>\n<\/td>\n
\n
BloX Webhook to device<\/p>\n<\/td>\n
\n
N\/A<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Plugins & Scripts<\/h3>\n
\n
Sisense BloX<\/a><\/li>\n
Percent Complete Circle and Indicator<\/a><\/li>\n
Stream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\n
Display BloX Widgets Horizontally<\/a><\/li>\n
Widget Title Style Plugin<\/a><\/li>\n<\/ol>\n"}}

Goals<\/h3>\nDecrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n

Optimize Your Cloud Investments with Sisense and Redshift<\/h2>\r\n\r\n\r\n

Optimize Your Cloud Investments with Sisense and Redshift<\/h2>\r\n\r\n\r\n

Goals<\/h3>\nDecrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n

Plugins & Scripts<\/h3>\n\nSisense BloX<\/a><\/li>\nPercent Complete Circle and Indicator<\/a><\/li>\nStream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\nDisplay BloX Widgets Horizontally<\/a><\/li>\nWidget Title Style Plugin<\/a><\/li>\n<\/ol>\n"}}

Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n

Goals<\/h3>\n
Decrease costs by optimizing device activity by monitoring and analyzing energy consumption.<\/p>\n

Plugins & Scripts<\/h3>\n
\n
Sisense BloX<\/a><\/li>\n
Percent Complete Circle and Indicator<\/a><\/li>\n
Stream Data Into a Widget with Sub-Second Refresh<\/a><\/li>\n
Display BloX Widgets Horizontally<\/a><\/li>\n
Widget Title Style Plugin<\/a><\/li>\n<\/ol>\n"}}

IOT Live Energy

High Level Design

Overview

Explore Dashboard