Tale of Data leverages Artificial Intelligence
to enhance Business People efficiency
in Big Data Preparation and Analytics
Tale of Data Main Features
Connection to any Datasource
You can import data from any file
(CSV, Parquet, JSON, XML, Excel,...), from any relational or noSQL database.
Since Tale of Data leverages
Apache Spark Framework,
your data can be processed directly
in your HADOOP cluster.
Dozens of Point and Click Data Transformations
With Tale of Data, dozens of instant transformations are at your fingertips.
Solving Data Quality issues
and preparing your Data for analytics are a breeze.
You don't need to be
a software engineer or a Data Scientist
to do the job!
Tale of Data provides advanced joins to add new columns
to any dataset:
Exact, Fuzzy, Phonetic, Full-Text...
Joining heterogeneous data
has never been so easy.
Multi-Criteria and Mutli-Strategy Data Depuplication
First, select the columns to be used
for row comparisons. We can select
as many columns as we want.
Then, for each selected column,
just specify the algorithm to be used
to compare cell values
(Phonetic, N-Gram, Fuzzy,...).
Data Transformation Recommendation Engine
Just select relevant text fragments
in any cell and the recommandation engine will automatically make relevants suggestions, such as:
extract a word or a year from a date,
split the cells, ...and so on.
Let Tale of Data guide your Data Preparation Journey : what used
to take weeks will be done in minutes.
Instant Data Visualization using Drag'n'Drop
With Tale of Data, instant data visualization is a breeze.
You just need to choose a chart and to drag and drop the relevant dimensions and measures.
Bar charts, Pie & Donuts charts, Bubble charts, Geographic Maps are at your fingertips.
The Tale of Data Processing Engine runs in HADOOP, by leveraging the Apache Spark Framework.
The engine uses Off-Heap Memory Management to eliminates the Garbage Collector pressure, boost performances and enhance scalability.
Can Run in HADOOP
The Tale of Data Processing Engine runs in HADOOP, by leveraging
Apache Spark Framework.
The engine uses Off-Heap Memory Management to eliminate
the Garbage Collector pressure, boost performances
and enhance scalability.
SaaS or on-Premises
Tale of Data can be used
as a Service (SaaS) :
which means lower IT costs
for hardware and painless upgrades.
On the other hand,
if the SaaS Mode is not an option,
Tale of Data can be deployed
to your own Information System:
as a standard Java Web Application,
it runs in any JEE Application Server, including Apache Tomcat.