Connectors for virtually anything

Minely has developed a wide variety of proprietary connectors that make it easy to connect to virtually any data source. Unlike traditional BI, no data warehouse is needed. Using Minely’s Just-In-Time Data Processor engine, data is processed as it happens.

Blazing Fast Distributed Analytics

Minely harnesses the power of Apache Spark –  a fast and general engine for large-scale data processing. It can run in Hadoop clusters through YARN, Mesos, HDInsight, Databricks or Spark’s standalone mode. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning. Spark currently holds the world record for the fastest sort on 100TB of data.

Data Blending

Minely empowers the user to clean, manipulate, query and analyse data coming from different data sources using the workflow engine. Minely intelligently optimises the execution path of a workflow by moving code close to the data as much as possible.  Minely supports a variety of data sources such as Transactional data, CRM, Unstructured social media data, Weather, Holiday calendars & Sensor data.

By blending all these data sources together, it is now possible to ask questions which were never answered before.

Powerful Workflows

Minely offers an innovative workflow engine that adapts to industry specific needs with our innovative workbench that allows you to customise data pipelines and processes using an intuitive drag and drop designer. The workflow engine has been engineered with cutting-edge distributed in-memory processing to easily handle big data workloads.

As more data is being collected and becoming available, it has become critical for decision makers to blend these data sources together to get deeper insights. Our visual canvas provides a drag-and-drop user interface, which enables the user to control the entire data pipeline from input to output.

Machine Learning

Minely utilises Spark’s Machine Learning algorithms and makes it easy for users to build sophisticated, large scale predictive models that cover a broad set of scenarios. Minely supports a wide variety of algorithms for feature extraction, clustering, classification, recommendations & regression.

Flexible Segment Engine

Minely enables users to visually segment business entities such as customers and products. The SEGMENTER applies behavioural analytics and can also be integrated with Minely’s machine learning module for automatic segmentation (a.k.a clustering).

  • The SEGMENTER module helps users analyze data objects (such as Customers, Products, Prices, etc…) according to their behavior.
  • Building a segment is quick and easy due to the underlying references between objects and events. The segment processes each event (behavior) on a specific time window.
  • Minely keeps track of the segment lifecycle by identifying whose entering or leaving a specific segment.
  • Minely SEGMENTER allows businesses to create a specific segment for their needs – location, behavior, external data sources such as weather, buying patterns, etc.
  • The SEGMENTER has seamless integration with the actions engine, which allows a business user to easily target actions on specific segments.

Real-time Visual Insights

Quickly gain visual insights through interactive dashboards with support for compare with past analysis, drill down and searching.

With Minely’s distributed query processor, it is very easy to visualise large datasets. It is also possible to blend data on-the-fly, within the dashboard, from multiple data sources, without the need to copy the data in a data warehouse.

The VISUAL INSIGHTS enables the user to build powerful dashboards through data flows, giving them a high level of flexibility.

Insights can shared securely with people inside or outside the organisation with different data permission levels.

The different visualisation widgets act as links to other visual insights, helping the users get a deeper understanding of the whole picture.

The VISUAL INSIGHTS utilise an in-depth text search to help the user identify and discover exactly what they’re looking for.

Predictive Analytics

At its core, Minely continuously improves and learns as your business grows. Using several machine-learning algorithms together with R Integration, Minely’s workflow engine is empowered to answer bigger questions regarding the past trends and forecast possible scenarios. Minely leverages the power of in-memory data processing and distributed computing to massively process and analyse huge amounts of data which is the key to gain competitive advantage.

Automated Actions

Traditional BI actions often involves running a set of reports and then manually taking an action based on the results. Minely solves this labor-intensive task by automating BI actions. There are several use cases for this feature, such as:

  • Offer automated and targeted coupons
  • Trigger automated business alerts on trending products
  • Real-time in-app offers or bonuses

All actions could be easily integrated with existing systems such as loyalty scheme systems, bonus engines, etc. Actions could be triggered in the different ways. The following are some examples:

  • Change in object state (e.g. customer state)
  • Targeted actions based on an external event
  • Time based actions

Learn how Minely can help you

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