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Big Data

What is Big Data?

     Big data is a field that analyzes and extracts information from data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.When we handle big data, we may not sample but simply observe and track what happens. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value. Josh Dreller defines Dig Data as something too big to fit in an Excell sheet.

     Big data has increased the demand of information management specialists so much so that Software AG, Oracle Corporation, IBM, Microsoft, SAP, EMC, HP and Dell have spent more than $15 billion on software firms specializing in data management and analytics. In 2010, this industry was worth more than $100 billion and was growing at almost 10 percent a year: about twice as fast as the software business as a whole.

     Especially since 2015, big data has come to prominence within business operations as a tool to help employees work more efficiently and streamline the collection and distribution of information technology (IT).Big Data can offer many benefits such as new possibillities, more effiency in marketing, better customer service etc.

Big data can be described by the following characteristics:

Volume, Variety, Velocity, Veracity, Value and Variability.

 

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MICROSOFT POWER BI

Microsoft's solutution for Analytics.

      Microsoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, analyzing, visualizing and sharing data. Power BI's user interface is fairly intuitive for users familiar with Excel and its deep integration with other Microsoft products makes it a very versatile self-service tool that requires little upfront training. 

      Power BI is used to find insights within an organization's data. Power BI can help connect disparate data sets, transform and clean the data into a data model and create charts or graphs to provide visuals of the data. All of this can be shared with other Power BI users within the organization. The data models created from Power BI can be used in several ways for organizations, including telling stories through charts and data visualizations and examining "what if" scenarios within the data. Power BI reports can also answer questions in real time and help with forecasting to make sure departments meet business metrics.

Power BI components that help users create and share data reports:

    •Power Query: a data mashup and transformation tool

    •Power Pivot: a memory tabular data modeling tool

    •Power View: a data visualization tool 

    •Power Map: a 3D geospatial data visualization

    •Power Q&A: A natural language question and answering engine

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GOOGLE BIG DATA ANALYTICS

Google's solution for Big Data Analytics.

     Google Cloud Platform (GCP), offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. Alongside a set of management tools, it provides a series of modular cloud services including computing, data storage, data analytics and machine learning. Registration requires a credit card or bank account details.

Some of Google Gloud Platform's services about Dig Data are BigQuery ( a scalable, managed enterprise data warehouse for analytics), Cloud Dataflow  (a managed service based on Apache Beam for stream and batch data processing and Cloud Dataproc (a Big data platform for running Apache Hadoop and Apache Spark jobs).

     Accelerate time to insights and leave the complexities of data analytics behind with Google Cloud Platform (GCP). Realize the benefits of serverless, integrated, and end-to-end data analytics services that surpass conventional limitations on scale, performance, and cost efficiency. BigQuery lets you analyze gigabytes to petabytes of data using ANSI SQL at blazing-fast speed and provides REST-based APIs for easy integration with other applications. Your developers can create analytics applications in familiar programming languages like Java, Python, C#, Go, Node.js, PHP, or Ruby. Cloud Pub/Sub lets you ingest millions of events per second from anywhere (and lets you publish it anywhere) in the world via an open API. Cloud Dataflow enables faster streaming and batch data pipeline development without compromising robustness, accuracy, or functionality. Enhance your BI solution with fast dashboards in Data Studio, powered by BigQuery BI Engine.

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ORACLE ANALYTICS CLOUD

Oracle's solution for Big Data.

     Oracle Analytics Cloud is a scalable and secure public cloud service that provides a full set of capabilities to explore and perform collaborative analytics for you, your workgroup, and your enterprise.

With Oracle Analytics Cloud you also get flexible service management capabilities, including fast setup, easy scaling and patching, and automated lifecycle management.

Built on a high-performance platform with flexible data storage, Oracle Analytics Cloud provides a complete set of tools for deriving and sharing data insights, such as Data preparation, Data flow, Data discovery, Data visualization and Data collaboration.

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SAP ANALYTICS CLOUD

SAP's solution for Big Data Analytics.

      SAP Analytics Cloud (or SAP Cloud for Analytics) is a software as a service business intelligence (BI) platform designed by SAP that uses machine learning technology. Analytics Cloud is made specifically with the intent of providing all analytics capabilities to all users in one product. SAP Analytics Cloud allows data analysts and business decision makers to visualize, plan and make predictions all from one secure, cloud-based environment. SAP claims this differs from other BI platforms, which often require data to be integrated from various sources and users to jump between different applications when performing tasks, such as creating reports. With all the data sources and analytics functions in one product, Analytics Cloud users can work more efficiently, according to SAP. The key functions are accessed from the same user interface that is designed for ease-of-use for business users.

Some of its key features are:

     • Integration with SAP Analysis for Microsoft Office: This includes read and write functions for users who want to import data and work in readily familiar environments.

     • Data locking and enhanced data access rights: Used for forecasting processes, where responsibilities held by planners are enforced by data locking and additional locked states (open, locked and restricted) are defined by enhanced data access rights.

     • Predictive analytics: Implements machine learning to perform guided analysis using Smart Discovery, transformations and insights.

     • Access to on-premise and cloud data: Provides real-time access to SAP applications such as HANA, as well as non-SAP applications for on-premise and cloud locations.

     • Embedded analytics: Allows for users to access analytic features such as what-if analysis and ad-hoc.

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IBM WATSON ANALYTICS

IBM's solution for Analytics.

     IBM Watson Analytics is an intelligent, self-service data analysis and visualization application for discovering patterns and insights in your data. It guides you through the process of discovery and automates the predictive analysis and related cognitive processes that comes afterward.

     Because of the natural language processing capability of IBM Watson Analytics, you can interact with your data as if you are having a conversation with it. As such, you can extract answers from structured and unstructured information with ease.

Furthermore, IBM Watson Analytics lets you instantly find new and emerging trends in your data. The service even presents it in a visual manner through your dashboards so you can detect patterns faster.

IBM Watson Analytics Features :

      •Natural Language Dialogue

      •Automated Predictive Analysis

      •One-Click Analysis

      •Smart Data Discovery

      •Advanced Analytics

      •Self-Service Dashboards

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This Edureka video on Big Data Technologies will provide you in-depth knowledge on Big Data Tools.

This video will help you understand different types of Big-Data Technologies and trending Big-Data Tools in IT Industries.