=Paper=
{{Paper
|id=Vol-1670/paper-08
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1670/paper-08.pdf
|volume=Vol-1670
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1670/paper-08.pdf</pdf>
<pre>
 Massively distributed BIG DATA management
                 for Enterprises

    Franz Faerber1 , Jonathan Dees1 , Westenberger Eric1 , and Marc Hartz1

                             SAP SE, Germany
    {franz.faerber,jonathan.dees,eric.westenberger,marc.hartz}@sap.com

    More and more companies recognize the value of digitalized information and
data for their business. We see a clear trend that business models are adapted or
completely changed by putting data into the center of their operations. Managing
these data from infrastructure, data ingestion, data consistency, data manipula-
tion to data consumption becomes therefore even more critical especially when
considering the huge amount of data, which are created in enterprises (BIG
DATA). There are many systems and infrastructures available which deal with
BIG DATA focusing on different aspects of the problem space like massive dis-
tribution, machine learning, and other topics. Making BIG DATA technologies
available for enterprises in a way, that they can build their business on top is still
an open challenge. In this presentation we demonstrate on the example of SAP
HANA BIG DATA what enterprise readiness means for BIG DATA solutions
and how the architecture of such a system looks like. Beside the enterprise fea-
tures, special focus will be set to the extensibility of the system and the ingestion
process.

</pre>