Post on 08-Jan-2017
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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.
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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.