PowerPoint Presentation

Water and Big DataAn analogy with water to help understand Big Data.

Data seem to be everywhere. Data has emerged as the worlds vital resource for decision making and can be called as elixir of digital world.

The sheer volume of the data is colossal.Every day, we create around 2.5 Quintillion bytes of data.Data, Data, Everywhere..

Water is the elixir of life. It the most essential, pervasive and vital element for all known forms of life.

Water is everywhere:Above the Earth in the air and clouds,On the surface of the Earth in rivers, oceans, ice, plants, in living organisms, and Inside the Earth in the top few miles of the ground.Water, Water, Everywhere....Ubiquitousness

Source: IBM

Generated from anything and everything. Some sources feed data unceasingly in real time: sensors, posts to social media sites, digital pictures and videos, e-Commerce transactions, cell phone GPS signals, just to name a few. However, only negligible percentage is being been processed as meaningful info from that.

There is a crunch for relevant data when and where we need and in the reliable form that we need.

Some 97% of the water on the earth is salt water.Two percent of the water on earth is glacier ice at the North and South Poles.Less than 1% of all the water on earth is fresh water that we can actually use.

Majority of the population are struggling to get usable water.Spread and Yield

http://pennystocks.la/internet-in-real-time/

Big data comes in two distinct forms DATA AT REST and DATA IN MOTION

Essentially there are two types, Static Water (Lentic) and Flowing Water (Lotic). The characteristic of water can be determined based on whether water is at rest (Hydrostatics) or water is at motion (Hydrodynamics).Flow

Data at Rest is the term used for persisted data.This refers to data that has been collected from various sources and is then analyzed after the event occurs. The point where the data is analyzed and the point where action is taken on it occur at two separate times.Similar to Lentic System, typical characteristics of data at rest are VOLUME AND VARIETYVOLUME is the characteristic of data at rest that is most associated with Big Data.The second characteristic of data at rest is VARIETY of data, meaning the data represents a number of data domains and a number of data types such as structured data or unstructured like text, images, video or any other raw data.

Lentic systems (meaning to make calm) are still / slow moving water bodies like lakes, ponds, and inland wetlands.The characteristics of water body are highly dependent on the size of the water body and on the climatic conditions in the drainage basin.Typically they are characterized by water volumes, residence times and fluxes. Rest

Data in Motion is the term used for data as it is in transit.Data in motion is processed and analyzed in real time, or near-real time, and has to be handled in a very different way than data at rest. Data in motion tends to resemble event-processing architectures, and focuses on real-time or operational intelligence applications.As observed in Lotic System, typical characteristics of data in motion are VELOCITY and VARIABILITY.The VELOCITY is the rate of flow at which the data is created, stored, analyzed, and visualized.Big Data VELOCITY means a large quantity of data is being processed in a short amount of time.The second characteristic for data in motion is VARIABILITY, which refers to any change in data over time, including the flow rate, the format, or the composition.

Lotic systems (meaning to wash) are Water AT Motion.

They are running water, where the entire body of water moves in a definite direction.

These may comprise brooks, streams, rivers and springs.Movement

Big Data is typically measured by VOLUME(key attribute of data at rest ) and VELOCITY (key attribute of data in motion )

VOLUME-As mentioned earlier, for big data, volume of data rules and so is the measuring units.

We have kilobyte, megabyte, gigabyte, terabyte, petabyte, exabyte, zettabyte, and yottabyte (1,000,000,000,000,000,000,000,000 bytes) to express the data volume. VELOCITY-Data In Motion is widely used to represent the speed at which large volumes of data are processed. Big data can hit fast. Just imagine dealing with petabytes of data transactions per second. Big data solutions should handle and process those rapidly arriving data.

Water is measured based on whether water at rest or water in motion.

Water at rest is measured in units of volume.

Water in motion is measured in units of flow.

Measure

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