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E-Commerce Platforms

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EinsteinDB is a new DBMS that we are developing in San Francisco able to tune and optimize itself automatically without any human intervention other than selecting the target objective (OLAP/OLTP) function on relativistic start-up. \ EinsteinDB's core architecture is a Postgres-compatible HTAP system. It uses HyPer-style MVCC over Apache Arrow in-memory columnar storage.

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    Predicting multiple metrics for queries

    This first component compresses all of the past metric data in the repository into a smaller set of metrics that capture the distinguishing characteristics for different workloads. It uses factor analysis (FA) to model each internal runtime metric as linear combinations of a few factors.

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    4+

    Founders

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    11978

    Update heavy operations/sec

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    120 million 1 KB causet

    50 percent reads and 50 percent updates.

Knowledge Graphs built on the EinsteinDB platform are able to run queries of unprecedented complexity to support predictive analytics that help companies make better, real-time decisions.

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We Offer Professional Solutions For Business

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Data Analytics

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AI & ML Development

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Data Science

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Predictive Analytics

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Software Development

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Elastic Solutions

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bannerHow It's Work

The Data Science Process

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1
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Frame the Problem

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2
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Collect the Raw Data

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3
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Process the Data

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4
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Explore the Data

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5
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Perform In-depth Analysis

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6
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Communicate Results

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Our Data Scientist

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Merv Adrian

Data Management
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Kirk Borne

Data Scientist
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Carla Gentry

Analytical Solutions
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Marie Curie

Data Scientist
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What Our Clients are Saying?

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Write Optimizaption

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