Introduction to Database Design and Management - ISYS114

Running head: INTRODUCTION TO DATABASE DESIGN AND MANAGEMENT
Introduction to Database Design and Management
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INTRODUCTION TO DATABASE DESIGN AND MANAGEMENT1
Concept of Data Lake along with Current Application
A data lake could be defined as a repository of storage, which would be able
to hold a huge amount of data within their present format. A data lake stores data
from various sources in an unstructured way (Terrizzano et al., 2015). There would
not be a form of hierarchy or any form of organized positioning of the individual
pieces of data. The data lake would always store the data in their present format. In
addition to this, the data lake would accept and thus retain data from different kinds
of data sources, support their present schemas and data types. The use of the data
would only be needed whenever they would be ready to be used. These data lakes
would thus be helpful for the generation and processing of data.
One of the current application of Data Lake is Amazon Web Services (AWS)
Data Lake. The AWS platform provides an agile set of services in order to store,
move and analyse data (Madduri et al., 2014). AWS helps in the importing of data in
real time. They store the data in a secure format that would range from gigabytes
to exabytes. AWS would also be able to analyse the data based on a broader form
of selection based on search engines and analytic tools. The impact of machine
learning would be able to forecast the future outcomes of the analysing of data and
thus would also be able to prescribe actions based on them (Gupta et al., 2015).
AWS helps in offering a broader set of analytic tools. These tools would be
highly efficient for performing analysing of data with the aid of open formats and
standards. The raw data could be stored in a format based on the choices of the
organization (Kim, Trimi & Chung, 2014). The possible formats for the storing of
data in the data lake are CSV, Grok, ORC, Parquet and Avro. AWS provides the
flexibility to perform analysing on the data in various number of ways that includes
interactive SQL queries, data warehousing, processing of big data and real-time
analytics. The breadth of the services based on data analytics would be able to
ensure the needs of the organizations. Based on the usage of data analytics, the
AWS services would be able to meet the use cases of existing and future analytics
(Wong & Kerkez, 2016). The AWS data lake would also be able to store and retrieve
any quantity of data based on the factors of unmatched stability and thus also be
able to deliver durable solutions. The AWS platform would also provide storing
services across multiple data centres based on three zones of availability based on