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HUAWEI TECHNOLOGIES CO., LTD.Tijo Thomas , Nijel S F

Bigdata – Business Opportunities

Contents Introduction

Big Data Market

Business Domains Solutions

Cloudify

Cluster Modelling

Data Governance

Q & A

Data !!

According to Gartner there will be nearly 26 billion devices on Internet of Things by 2020

Data Big data is when the data itself becomes part of the problem.

Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them

Big Data - Change from Web Technology. Traditional software stacks have been application oriented, and

applications were built in more or less the same way. The Data is represented to suit the Application.

Data first, application second

Applications and Solutions are Have be tailored to datatype and workload.

Given the differences in datatypes – and workload context – this in turn means that there are going to be a number of different solutions and applications.

Money from Big Data

The main point of using big data analytics should be to grow your revenue

Business Domains1. Solutions2. Cloudify3. Cluster Modelling4. Data Governance

Big Data Trends in 2017 Big data becomes fast and approachable

In memory computing Kudu, Impala, CarbonData

Purpose-built tools for Hadoop become obsolete

Analytics on all data purpose-built for Hadoop and fail to deploy across use cases will fall

Architectures mature to reject one-size-fits all frameworks

use case-specific architecture design combine data-prep tools, Hadoop Core and analytics platforms

Convergence of IoT, cloud, and big data

Increasing share of this data is being deployed on cloud services demand is growing for analytical tools to connect to and combine cloud-

hosted data sources

Big Data solutions

I have Data and I want xyz result ! Can some one tell what to use ?

Here comes the

solutions

The Era of solution architects risesEnterprises looks for a pre defined solution for a particular use case.

HUAWEI TECHNOLOGIES CO., LTD. Huawei Confidential 9

This is a ‘one-size-fits-all’ category that could include anything - Bernard Marr Leading Business and Data Expert

Web Analytics Web analytics is the measurement, collection, analysis and reporting of web data for purposes

of understanding and optimizing web usage. can be used as a tool for business and market research, and to assess and improve the effectiveness of

a website. Estimate how traffic to a website changes after the launch of a new advertising campaign. Provides information about the number of visitors to a website and the number of

page views. Helps gauge traffic and popularity trends which is useful for market research.

CIick Stream Analysis What is the most efficient path for a site visitor to research a product, and then buy it? What products do visitors tend to buy together, and what are they most likely to buy in the

future? Where should I spend resources on fixing or enhancing the user experience on my website?

Stream feeds into HDFS with Flume

Use SPARK to build a relational view of the data

Use SPARK to query and refine the data

Visualize data with Tableau

Tableau does not have a official HBase connector.

Log analysis - > ELK stack Flume ingests log data from

multiple web servers into a centralized store (HDFS, HBase) efficiently.

Along with the log files, Flume is also used to import huge volumes of event data produced by social networking sites like Facebook and Twitter, and e-commerce websites like Amazon and Flipkart.

Flume supports a large set of sources and destinations types.

Flume can be scaled horizontally.

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Big Data In CloudWhy ?

Auto Scaling

Low TCO

Zero maintenance

Cloud Services

Low Storage Cost

Big Data In Cloud Companies standardized on Big Data tools including Spark, Hadoop/MapReduce, Hive,

and Pig, will find a natural transition to Cloud

The major motive is to use the available cloud services such as OBS, RDS etc. along with Big Data Technologies

Many solutions will come as a box up by combining available services in cloud.

Customers will demand to cloudify the applications and use cloud services.

Data Governance1) Enable the lake

Managed ingestion

Metadata management

2) Govern the data

Data lineage

Data privacy and security

Data quality

Data lifecycle management

3) Engage the business

Data catalog

Self-service data preparation

4) Pipelining and ETL

Data movement across stores

Periodic aggregation

Cluster modelling and Maintenance

Facilitating accurate migration of data from traditional data storage systems to Hadoop.

Analytics & Visualization Help organizations to

process large amount of complex data visualize it to meaningful and user readable form easily analyse business data and perform trend

analysis.

Thank youwww.huawei.com

Copyright©2011 Huawei Technologies Co., Ltd. All Rights Reserved.The information in this document may contain predictive statements including, without limitation, statements regarding the future financial and operating results, future product portfolio, new technology, etc. There are a number of factors that could cause actual results and developments to differ materially from those expressed or implied in the predictive statements. Therefore, such information is provided for reference purpose only and constitutes neither an offer nor an acceptance. Huawei may change the information at any time without notice.