10 most effective big data technologies

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Big Data Technologies



Big data is simply large amount of data

Data can be structured or unstructured

Data is analysed to gain insights

Insights help in making better business decisions

Helps management to take tactical decisions regarding the future of their

business

What is Big Data?



Big data technologies help organizations take out meaningful information out

of gigabytes of data.

They are important tools to organize and analyse large volumes of data.

Many big data technologies are available today, invented by the tech

leaders of the world.

Big Data Technologies



A part of advanced analytics, which makes predictions about what will happen in future.

Analysis is done through technology. Uses various techniques like statistics, modelling, artificial intelligence,

machine learning, data mining and others. All these methods are used to predict the uncertainties of business. Helps organizations to improve business performance and mitigate risk.

Top 10 Big Data Technologies


1. Predictive Analytics


Often known as Non-SQL, Non-relational or not, only SQL database. Provides a platform for businesses to store and retrieve data by finding

relationships between various data groups. First introduced in the late 1960s. Gained popularity in the 21st century, when companies like Facebook,

Google, Amazon started using them. Simple in design and provides better control over available solutions.



2. NoSQL Databases


Collects information and knowledge from various sources like databases, file systems, streams, APIs, etc

Delivers useful insights based on a specific context or need Information is collected through extensive search in these platforms and

intelligent search results are delivered. Simple and usable technology



3. Search and Knowledge Discovery


An event processing engine where the event can be fed in real-time from a single stream of data or multiple streams.

Data is then filtered and analyzed to get multiple outputs which can be used in business.

Data can be fed from multiple sources also like applications, devices, sensors, operation system, websites, etc



4. Stream Analytics


An infrastructure software that slides between applications and data sources.

Processes enormous amounts of data very fast to deliver real time results. Extremely good for high-performance transactions, real-time streaming,

comprehensive data processing and a variety of other tasks. In most cases, distributes data between dynamic random access memory

(DRAM), Flash and SSD of a computer system.



5. In-memory Data Fabric


A technology where data is stored in various layers which are often similar in structure

Ensures higher performance and lower redundancy In most cases, location agnostic which help to improve reliability and

reduce the complexity of different layers of data.



6. Distributed File Stores


A technique by which data is retrieved and manipulated Does not take into account the technical details about the data like where

is it located or how was it found. Data is processed in real time or near real time basis.



7. Data Virtualization


Data are combined using technical and business intelligence. Processed from different sources to bring out meaningful information. Information output is often termed as ‘trusted’ because of the way the

same is processed. This method uses solutions like Amazon Elastic Map Reduce (EMR), Apache

Hive, Apache Spark, Couch base, Hadoop etc.



8. Data Integration


Manipulates data and makes it suitable for further processing and analysis. Manipulation is done through various tasks, both manual and automated. The preparation work is tedious, time-consuming and routine. Main intention is to reduce the burden of shaping and cleaning a diverse

set of high volume data for the analysts.



9. Data Preparation


Refers to cleansing a large volume of data to ensure the output is of high quality.

The high-quality data can then be used for operations, decision making, and planning.



10. Data Quality


Big Data is here to stay. It’s growing faster than ever. By 2020, 1.7 megabytes of new information will be created every

second of every human on earth (Prediction).

Total accumulated data today is 44 zettabytes. It will grow ten times by 2020.

Every second 40,000 search queries are made on Google.

Future Roadmap


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10 most effective big data technologies

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