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Best Time Series Intelligence Software

What is Time Series Intelligence Software?

Time Series Intelligence software also known as time series analytics software is used to analyze and extract significant business insights and trends from time series data. It allows users to identify patterns within massive data.

How to compare different Time Series Intelligence Software?

“Ease of Setup”, “Ease of Admin”, and “Quality of Support” is used to determine the difference between different Time Series Intelligence software. Their impact on the users satisfaction and software performance determine which software is better.

Ease of Setup

8.7 out of 10 on average

Ease of Admin

8.5 out of 10 on average

Quality of Support

8.4 out of 10 on average
  • Proappslab


    TrendMiner is a Web Based self-service analytics Platform for Process Manufacturing. It is a software company that delivers self-service data analytics to help cross-site teams to collaborate and improve their performance. Its key features are: -
    1. Analysis
    2. Analytics
    3. Data Mining
    4. Modeling
    5. Data Visualization and Unification
    6. Data Management

Learn More About Time Series Inteliigence -

What does Time Series Intelligence software?

Time series intelligence software can also be called time analytic software. As it can identify patterns within massive, continuous time series data sets to perform reporting, forecasting, and predictive analysis. It can analyze large amounts of data to give accurate analysis of various things required by business. It can be used to collect various data from the machine to set up warnings when there is a problem with the machine. It can be done using large amounts of data which is analyzed by Time series intelligence software.

What are the 4 types of time series models?

  1. It refers to different ways to measure timed data. Types are:-
  • Autoregression 
  • Moving Average
  • Autoregressive Integrated Moving Average
  • Seasonal Autoregressive Integrated Moving-Average

What are the 4 components of time series?

  1. Four components of time series are as follow:-
  • Secular trend:- It describes movement along the long term.
  • Seasonal variations:-  It represents seasonal changes.
  • Cyclical fluctuations:- It corresponds to periodical but not seasonal variations.
  • Irregular variations:- Other nonrandom sources of variations of series.

Why is it called a time series?

  1. It is a collection of observations of well-defined data items obtained through repeated measurements over time.

What is the basic concept of time series?

  1. Time series is a collection of basic well-defined data items obtained through repeated measurements over time.