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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. layout: publication title: Publication subtitle: > Road to Freedom in Data Analytics link-name: Vision Paper at EDBT 2016 img-thumb: assets/img/screenshot/vision.png authors: Divy Agrawal, Sanjay Chawla, Ahmed Elmagarmid, Zoi Kaoudi, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiane╠ü-Ruiz, Nan Tang and Mohammed J. Zaki year: 2016 month: 03 day: 15 link-paper: assets/pdf/paper/vision.pdf link-external: false

The world is fast moving towards a data-driven society where data is the most valuable asset. Organizations need to perform very diverse analytic tasks using various data processing platforms. In doing so, they face many challenges; chiefly, platform dependence, poor interoperability, and poor performance when using multiple platforms. We present RHEEM, our vision for big data analytics over diverse data processing platforms. RHEEM provides a threelayer data processing and storage abstraction to achieve both platform independence and interoperability across multiple platforms. In this paper, we discuss our vision as well as present multiple research challenges that we need to address to achieve it. As a case in point, we present a data cleaning application built using some of the ideas of RHEEM. We show how it achieves platform independence and the performance benefits of following such an approach.