Azure Data Lake Analytics Features

Facilitates analysis of high-volume, real-time data.

Allows user to query data through query languages like SQL.

View and track pertinent metrics to find patterns and gain insights from data

Predict future data based on historical data sets

Interact with data visualization elements, such as charts and graphs, to drill down into data

Aligns processing and distribution workflows on top of Apache Hadoop

Aligns processing and distribution workflows on top of Apache Spark

Integrates data from multiple external databases.

Facilitates the dissemination of collected big data throughout parallel computing clusters.

Receive data and information in real time

Import, collect, and capture data from multiple sources

Review data from past periods to reveal recurring tendencies and predict future performance

Provides varying estimates based on different scenarios

Apply statistical/mathematical models to sets of data

Merge data from multiple sources to a single data set

Set up connections to third-party platforms to improve business processes

Processes data and represents interpretations in a variety of graphic formats.

Strings together specific functions and datasets to automate analytics iterations.

Isolates certain datasets and facilitates management of data access.

Allows big data tool to run and record data within external applications.

Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations

Discover and connect variety of data sources to the application for analysis

Central repositories of integrated data from various sources

Assemble applications and processes by dragging over and arranging pre-built components

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Connect to big data sources

Generate one-off reports that meet information requirements

Alter the layout and content of reports

System alerts about the need to escalate an issue or request

Sample files or documents that could be customized as needed or used as is

Form predictions based on past and present data/trends

Move from one database to another, or upgrade the version of database software being used

Translate EDI formats into data suitable for use with company applications.

Define levels of authorization for access to specific files or systems

Application programming interface that allows for integration with other systems/databases

Removes data that is incomplete, inaccurate, or irrelevant from a dataset

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Creation and customization of dashboards

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Protect sensitive data for digital privacy

Security protocol that ensures secure, encrypted communication over the internet, safeguarding sensitive data from unauthorized access

Provides a channel for team members to share media files, communicate, and work together

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Process and analyze large volume of data

Supports common databases such as MySQL and Oracle

Search and filter data across systems to locate required information by entering keywords or certain criteria

Use AI to generate content in the form of text, images, videos, etc.