3 min read

Sisense 7.0, Distilled IMPACT Behavioral Analytics Model, Gnocchi 4.2 release, and more in today’s top stories around machine learning, deep learning,and data science news.

1. Sisense 7.0 aids non-technical users to gain data expertise

Sisense announced the release of Sisense Version 7.0, which delivers an intuitive, visual, drag and drop interface for data preparation that is used by non-technical business users to easily find, add, and combine complex data sources.  

It delivers smart, machine learning-driven recommendations, helping guide users through the data preparation process by recommending use of specific fields to easily ‘mash-up’ data sources—saving time, unveiling new insights  and reducing the chance of errors. Leveraging advanced machine learning to allow for smart data preparation and visualization field suggestions presents a new step in making analytics accessible to everyone, regardless of technical skill or expertise.

For more information read the detailed coverage here.

2. Distilled Analytics releases distilled IMPACT behavioral analytics model

Distilled Analytics announced the release of Distilled IMPACT, which is an innovative approach to providing quantitative measurement of non-financial factors associated with for-profit investment that uses advanced behavioral analytics supported by artificial intelligence.

Distilled IMPACT platform quantifies non-financial activities using granular, discrete measures, particularly around human factors, to enable asset growth for impact investing by providing greater trust and transparency. It helps organizations understand impact by analyzing patterns of movement from aggregated and third-party data sources, revealing fundamental insight to human behavior.

3. IBM’s Watson Captioning to leverage Artificial Intelligence to Automate Closed Captioning Process

IBM leverages Artificial Intelligence (AI) to automate the closed captioning process as part of its latest Watson Captioning.

This new service will provide businesses with

  • A scalable solution which saves time and capital
  • Maximize productivity by streamlining workflows
  • An increased caption accuracy over time

The new IBM offering provides a seamless user experience via tools including Machine Generated Captions, Embedded Smart Layout, Watson Caption Editor and Live Captioning.

4. Gnocchi 4.2 released, with added features and performance

Gnocchi 4.2 is released. Gnocchi is an open-source time series database designed to handle large amounts of aggregates being stored while being performant, scalable and fault-tolerant. Let’s have a quick look at the features added in Gnocchi 4.2:

  • Wildcard can be used instead of metric name in Dynamic aggregates API.
  • Dynamic Aggregate API have a new method called ‘rateofchange’.
  • A new format for the batch payload is available to allow to pass the archive policy description
  • Gnocchi now strictly respects the archive policy configured timespan when storing aggregates.
  • A new date type ‘ datetime‘ is available for resource type attribute.
  • It provides a new /v1/influxdb endpoint that allows to ingest data from InfluxDB clients. Only write is implemented. This should ease transition of users coming from InfluxDB tools such as Telegraf.
  • Metricd exposes a new option called greedy (true by default) that allows to control whether eager processing of new measures is enabled when available.
  • Gnocchi API can act as Prometheus Remote Write Adapter to receive Prometheus metrics. The endpoint to configure in Prometheus configuration is:  https://<gnocchi-host-port>/v1/prometheus/write.
  • The deprecated dynamic aggregation (moving average) has been removed.

To know about these features in detail, visit its official website.

5. Podium Data releases Podium 3.2 to take its data lake catalog to the cloud

Podium Data Inc. brings self-service big data to the cloud with the release of its new version 3.2 of its Data marketplace.

Data Marketplace is a data catalog which is used with data lakes to eliminate the need for the extensive extraction and massaging procedures that characterize pure-Hadoop models. Podium promotes the software as providing self-service, on-demand access to quality data.

With the Podium 3.2 release, users can now combine on-premises and cloud data, as stated by the company. Podium architecture separates storage from computing to enable data taken from the data delivery teams to support multiple variations of an analytical application from a single store. With version 3.2, sources now include Amazon Web Services Inc. and Microsoft Corp. Azure clouds. Version 3.2 also permits assets inside and outside the cloud to be merged and joined.

For a detailed understanding of the Data Marketplace, visit the official website.

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