TIME-SERIES DATA RELIABILITY & OBSERVABILITY PLATFORM

Tame unreliable data, reduce overall data downtime, and make time-series analytics more trustworthy with Timeseer.AI. Empower your data teams to detect, prioritize, and investigate data quality issues before these hit operations. Timeseer.AI is already trusted by leading data teams from more than a dozen Fortune 5000 companies

 
 

“We don't need better models, we need better data.”

— Andrew NG

 
 

// Core Platform Components

REDUCE THE NUMBER OF DATA QUALITY INCIDENTS THAT HIT YOUR OPERATIONS WITH 10X

 
 

#1 DATA RELIABILITY SCORING AND PROFILING

  • 30+ built-in quality metrics that express the overall health of the underlying time-series data: variance drift, broken correlations, stale data, missing values, persist anomalies, IQR anomaly, ... 

  • Configure resources and processing flows with YAML

  • Define your own custom metrics and quality KPIs

 
 

#2 DATA MONITORING & OBSERVABILITY

  • Scan data proactively at scale & check quality

  • Segment data & create overviews of data downtime issues.

  • Define data SLAs and define quality gates

  • Collaborate on issues to improve Overall Data Effectiveness

 
 

#3 DATA QUALITY OPTIMIZATION, AUGMENTATION AND CLEANING

  • Input missing values

  • Filter out unwanted artefacts

  • Keep data volumes manageable while avoiding information loss

  • Align and transform data from different series

  • Define your own augmentation logic

 
 

#4 DATA CONNECTIVITY AND UNIFORMIZATION

  • Lower the burden of data integration 

  • Easily map to one uniform time-series data model

  • Organize time-series in series sets and asset templates

 

 

// Integrations

TIME-SERIES DATA OPS INTEGRATED IN YOUR MODERN DATA STACK

 

 

// Why?

It is crucial to get a grip on unreliable data before it impacts your operations. It only cost $1 to detect data downtime where it would have cost $10 to fix the problem and it would balloon to $100 of financial impact when it hits you operational.

 
 

// Benefits per role

HOW CAN TIMESEER.AI HELP YOU?

Data Officer

  • Define and monitor data SLAs to safeguard data hygiene
  • Set up a collaborative approach to examine and resolve data quality issues
  • Understand data downtime and overall data effectiveness
  • See where data quality issues impact decision making

Data Engineer (IT)

  • Simplify integration of time series data into your infrastructure
  • Integrate data quality checks into your data pipelines
  • Shift data cleaning and preparation steps upstream
  • Feed analytics apps with relevant context data
  • Get alerted when data downtime occurs

Automation Engineer (OT)

  • Safeguard a healthy data environment
  • Guarantee the desired data quality service level for your OT data
  • Get alerts for potential sensor failures

Data Scientist

  • Reduce time spent on data preparation and cleaning
  • Understand which data can be trusted for modelling purposes
  • Make manual, repetitive, reactive cleansing tasks more scalable and proactive job
  • Analyse data in context
  • Be aware of data complexity (eg. Non-stationarity) issues that are relevant for modelling choices
  • Make data preparation work reusable across projects and teams

Citizen Data Scientist

  • Understand which data can be trusted in your analytics work
  • Start your analytics journey by looking into relevant data quality events
  • Analyse data in context
  • Collaborate with E&I / automation staff to understand quality issues

// The Timeseer.AI Advisory Board

A GAME-CHANGER FOR OUR CUSTOMERS

To better serve our customers and the industry, we have established our trusted Advisory Board, a group of highly specialized thought leaders from various industries including hyperscalers, sensor solution providers, industrial/automotive/discrete manufacturing, and IoT. These leaders bring a diverse range of perspectives and intelligence to serve as our second brain, providing crucial expertise and key insights.

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