Big data

Ami Redwan Haq
Ami Redwan HaqFounder à Sentinel Solutions Ltd
Big Data
              Topics Covered

•What is Big Data?
•Big Data Laws
•Why Big Data?
•Industries using Big Data
•Current process/SW in SCM
•Challengesin SCM industry
•How Big data can solve the problems?
•Migration to Big data for an SCM industry
What is Big Data?

IBM Says                         WIKI Says
Every day, we create 2.5         Big data is more than simply a
quintillion bytes of data — so   matter of size; it is an opportunity
much that 90% of the data in     to find insights in new and
the world today has been         emerging types of data and
                                 content, to make your business
created in the last two years    more agile, and to answer
alone. This data comes from      questions that were previously
everywhere: sensors used to      considered beyond your reach.
gather climate information,      Until now, there was no practical
posts to social media sites,     way to harvest this opportunity.
digital pictures and videos,     Today, IBM’s platform for big data
purchase transaction records,    uses state of the art technologies
and cell phone GPS signals to    including patented advanced
name a few. This data is big     analytics to open the door to a
data.                            world of possibilities.
What is Big Data?
  Real Time
What is Big Data?
           Changes & Challenges

Big data is difficult to   The challenges include
work with using most
relational database        •capture
management systems         •curation
and desktop statistics     •storage
and visualization
packages, requiring        •search
instead "massively         •sharing
parallel software
running on tens,           •analysis
hundreds, or even          •visualization
thousands of servers".
What is Big Data?
    The key platform capabilities include
Visualization and                        Hadoop-based Analytics: Store any
Discovery: Discover, understand,         data type in the low-cost, scalable
search, and navigate federated           Hadoop engine to lower the cost of
sources of big data while leaving        processing and analyzing massive
that data in place.                      volumes of data.

                     Stream Computing: Continuously
                     analyze massive volumes of
                     streaming data with sub-millisecond
                     response times to take action in
                     real-time.

Data Warehousing: Store and              Text Analytics: Analyze textual
analyze large volumes of structured      content to uncover hidden
information with workload
optimized systems designed for           meaning and insight in
deep & operational analytics.            unstructured information.
What is Big Data?
          Supporting platform services
Accelerators: Faster time to           Application
value with pre-packaged                Development: Streamline the
analytical and industry-specific       process of developing big data
content.                               applications.

                   Information Integration and
                   Governance: Integrate, protect,
                   cleanse, govern, and deliver your
                   trusted information

Systems Management: Monitor            Reference
and manage your big data system        Architectures: Hardware,
for secure and optimized               networking and system software
performance.                           blueprints to accelerate time to
                                       value.
What is Big Data?
What is Big Data?
                  Examples

Examples include Big Science, web logs, RFID, sensor
networks, social networks, social data (due to the social data
revolution), Internet text and documents, Internet search
indexing, call detail records, astronomy, atmospheric science,
genomics, biogeochemical, biological, and other complex
and often interdisciplinary scientific research, military
surveillance, medical records, photography archives, video
archives, and large-scale e-commerce.
Big Data Laws
Big Data Laws
Why Big Data?
Why Big Data?
Why Big Data?
Industries using Big Data

•Banking                         •Energy and Utilities
•Risk and fraud management       •Smart meter analytics
•Customer analytics              •Asset management
•Transportation                  •Digital Media
•Logistics optimization          •Real-time ad targeting
•Traffic congestion              •Website analysis
•Healthcare                      •Retail
•Medical record text             •Omni-channel marketing
analytics                        •Click-stream analysis
•Genomic analytics               •Government
•Telecommunications              •Threat prediction and
•Call detail record processing   prevention
•Customer profile                •Fraud and abuse
monetization                     management
Industries using Big Data

 Big data = Big Return on Investment (ROI)
 While there is a lot of buzz about big data in the market,
 it isn’t hype.

                 Healthcare: 20% decrease in
                 patient mortality by
                 analyzing streaming patient
                 data

Telco: 92% decrease in           Utilities: 99% improved accuracy
processing time by analyzing     in placing power generation
                                 resources by analyzing 2.8
networking and call data         petabytes of untapped data
Current process/SW in SCM



              •ERP and SCP
              • WMS
              •TMS
              •MES
Current process/SW in SCM overcomes

Lack of visibility: Large corporations were left with too much inventory when the
recession hit and too little when demand picked up in 2009. “Users are looking at
applications like sales and operations planning, transportation management and
asset management applications that can be leveraged to track goods in motion,”
Eschinger says.

Enabling corporate strategy: Everyone wants to reduce costs, but increasingly
businesses are targeting supply chains to improve overall corporate viability,
especially customer service.

Total landed cost: Blame high transportation costs, increasing wages in emerging
markets and multi-channel sales and distribution strategies, but companies are
taking a more analytical look at what it costs to fill an online order versus a store
and what is the total cost to source in Mexico versus China.
Current process/SW in SCM
Challenges in SCM industry
Challenges in SCM industry

Customer service                               Cost control                                  Planning and Risk Management
Effective supply chain management is           Supply chain operating costs are under        Supply chains must periodically be
all about delivering the right product in      pressure today from rising freight            assessed and redesigned in response to
the right quantity and in the right            prices, more global customers,                market changes, including new product
condition with the right documentation         technology upgrades, rising labor rates,      launches, global sourcing, new
to the right place at the right time at        expanding healthcare costs, new               acquisitions, credit availability, the need
the right price. If only it were as simple     regulatory demands and rising                 to protect intellectual property, and the
as it sounds.                                  commodity prices. To control such costs       ability to maintain asset and shipment
                                               there are thousands of potential              security. In addition, supply chain risks
                                               metrics that supply chain organizations       must be identified and quantified. SCC
                                               can and do measure. Managers need to          members report that less than half of
                                               zero in on the critical few that drive        their organizations have metrics and
                                               total supply chain costs within their         procedures for assessing, controlling,
                                               organizations.                                and mitigating such risks.

                 Supplier/partner relationship                        Talent
                 management                                           As experienced supply chain managers
                 Different organizations, even different              retire, and organizations scale up to
                 departments within the same                          meet growing demand in developing
                 organization, can have different                     markets, talent acquisition, training,
                 methods for measuring and                            and development is becoming
                 communicating performance                            increasingly important. Supply chain
                 expectations and results. Trust begins               leaders need a thorough understanding
                 when managers let go of internal biases              of the key competencies required for
                 and make a conscious choice to follow                supply chain management roles,
                 mutually agreed upon standards to                    specific job qualifications, methods for
                 better understand current performance                developing future talent and leaders,
                 and opportunities for improvement.                   and the ability to efficiently source
                                                                      specific skill sets.
Challenges in SCM industry
How Big data can solve the
       problems?
How Big data can solve the
       problems?
How Big data can solve the
       problems?
How Big data can solve the
                   problems?
Digital Path to Purchase. The work           ecommerce. Amazon‘s work on
that McCormick is doing on Digital Path to   understanding demand insights of pantry
Purchase is breakthrough thinking. I         shopping is exciting. They are an early
would start there.                           leader in Big Data techniques. I would have
                                             them at the top of my list.




Listening. Text mining and ratings and       Safe and Secure Supply Chains. The work
review information at Bazaarvoice is a Big   at Eli Lilly on product serialization of
Data service. How could companies use        pharmaceuticals has direct applicability of
this data? How could it help in sensing      where we are headed on food safety. Food
early product failure? Only one out of ten   and beverage companies need to learn
companies that I talk to have ever heard     from this early work in Big Pharma.
of Bazaarvoice and the great work that       .
they are doing.
How Big data can solve the problems?

Supplier Sensing. The work at D&B on supplier sensing        Supply Chain Visibility. Let’s face it, we have been
is a great use of Big Data. I would include them in the      talking about supply chain visibility and agile supply
list and work with them on how consumer products             chains for many years, but it has just been talk. The
companies and retailers can sense supplier failure early     use of rules-based ontologies and learning
and use it to build stronger supplier relationships. We      systems to redefine supply chain visibility at Conair is
have talked about collaboration, but in reality, we have     a new way to think about sensing supply chains.
pushed costs and working capital back into the chain         While early, it is a great case study on how to use Big
increasing risk. The further back in the supply chain that   Data techniques to solve a tough problem.
we go and sense supplier health, the weaker the players
and the greater the risk to the brand. The work at D&B
is a great start to better understand this.

Demand Insights. The work at Kraft on consumer               Large-scale ERP. The race is on for global companies
insights, or the work at General Mills on downstream         to better serve emerging markets. These markets
data are Big Data problems in the making. While both         are fraught with disparate data that is often
companies today are using more conventional                  incomplete. These large consumer products
techniques, the size of the data is growing and insights     companies are also the companies with BIG DATA
can be gained on where we are headed.                        ERP systems. What are best practices for companies
                                                             in the ERP Petabyte club? How does the data
                                                             change? How does it affect maintenance and
                                                             upgrade cycles? And the definition of business
                                                             analytics?
Migration to Big data for an SCM
            industry
Migration to Big data for an SCM
            industry
Migration to Big data for an SCM
            industry
Migration to Big data for an SCM
            industry
The End


Thanks

Prepared by
RedwanulHaqChoyon
+8801611-222447
email: redwan.choyon@gmail.com
1 sur 31

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Big data

  • 1. Big Data Topics Covered •What is Big Data? •Big Data Laws •Why Big Data? •Industries using Big Data •Current process/SW in SCM •Challengesin SCM industry •How Big data can solve the problems? •Migration to Big data for an SCM industry
  • 2. What is Big Data? IBM Says WIKI Says Every day, we create 2.5 Big data is more than simply a quintillion bytes of data — so matter of size; it is an opportunity much that 90% of the data in to find insights in new and the world today has been emerging types of data and content, to make your business created in the last two years more agile, and to answer alone. This data comes from questions that were previously everywhere: sensors used to considered beyond your reach. gather climate information, Until now, there was no practical posts to social media sites, way to harvest this opportunity. digital pictures and videos, Today, IBM’s platform for big data purchase transaction records, uses state of the art technologies and cell phone GPS signals to including patented advanced name a few. This data is big analytics to open the door to a data. world of possibilities.
  • 3. What is Big Data? Real Time
  • 4. What is Big Data? Changes & Challenges Big data is difficult to The challenges include work with using most relational database •capture management systems •curation and desktop statistics •storage and visualization packages, requiring •search instead "massively •sharing parallel software running on tens, •analysis hundreds, or even •visualization thousands of servers".
  • 5. What is Big Data? The key platform capabilities include Visualization and Hadoop-based Analytics: Store any Discovery: Discover, understand, data type in the low-cost, scalable search, and navigate federated Hadoop engine to lower the cost of sources of big data while leaving processing and analyzing massive that data in place. volumes of data. Stream Computing: Continuously analyze massive volumes of streaming data with sub-millisecond response times to take action in real-time. Data Warehousing: Store and Text Analytics: Analyze textual analyze large volumes of structured content to uncover hidden information with workload optimized systems designed for meaning and insight in deep & operational analytics. unstructured information.
  • 6. What is Big Data? Supporting platform services Accelerators: Faster time to Application value with pre-packaged Development: Streamline the analytical and industry-specific process of developing big data content. applications. Information Integration and Governance: Integrate, protect, cleanse, govern, and deliver your trusted information Systems Management: Monitor Reference and manage your big data system Architectures: Hardware, for secure and optimized networking and system software performance. blueprints to accelerate time to value.
  • 7. What is Big Data?
  • 8. What is Big Data? Examples Examples include Big Science, web logs, RFID, sensor networks, social networks, social data (due to the social data revolution), Internet text and documents, Internet search indexing, call detail records, astronomy, atmospheric science, genomics, biogeochemical, biological, and other complex and often interdisciplinary scientific research, military surveillance, medical records, photography archives, video archives, and large-scale e-commerce.
  • 14. Industries using Big Data •Banking •Energy and Utilities •Risk and fraud management •Smart meter analytics •Customer analytics •Asset management •Transportation •Digital Media •Logistics optimization •Real-time ad targeting •Traffic congestion •Website analysis •Healthcare •Retail •Medical record text •Omni-channel marketing analytics •Click-stream analysis •Genomic analytics •Government •Telecommunications •Threat prediction and •Call detail record processing prevention •Customer profile •Fraud and abuse monetization management
  • 15. Industries using Big Data Big data = Big Return on Investment (ROI) While there is a lot of buzz about big data in the market, it isn’t hype. Healthcare: 20% decrease in patient mortality by analyzing streaming patient data Telco: 92% decrease in Utilities: 99% improved accuracy processing time by analyzing in placing power generation resources by analyzing 2.8 networking and call data petabytes of untapped data
  • 16. Current process/SW in SCM •ERP and SCP • WMS •TMS •MES
  • 17. Current process/SW in SCM overcomes Lack of visibility: Large corporations were left with too much inventory when the recession hit and too little when demand picked up in 2009. “Users are looking at applications like sales and operations planning, transportation management and asset management applications that can be leveraged to track goods in motion,” Eschinger says. Enabling corporate strategy: Everyone wants to reduce costs, but increasingly businesses are targeting supply chains to improve overall corporate viability, especially customer service. Total landed cost: Blame high transportation costs, increasing wages in emerging markets and multi-channel sales and distribution strategies, but companies are taking a more analytical look at what it costs to fill an online order versus a store and what is the total cost to source in Mexico versus China.
  • 19. Challenges in SCM industry
  • 20. Challenges in SCM industry Customer service Cost control Planning and Risk Management Effective supply chain management is Supply chain operating costs are under Supply chains must periodically be all about delivering the right product in pressure today from rising freight assessed and redesigned in response to the right quantity and in the right prices, more global customers, market changes, including new product condition with the right documentation technology upgrades, rising labor rates, launches, global sourcing, new to the right place at the right time at expanding healthcare costs, new acquisitions, credit availability, the need the right price. If only it were as simple regulatory demands and rising to protect intellectual property, and the as it sounds. commodity prices. To control such costs ability to maintain asset and shipment there are thousands of potential security. In addition, supply chain risks metrics that supply chain organizations must be identified and quantified. SCC can and do measure. Managers need to members report that less than half of zero in on the critical few that drive their organizations have metrics and total supply chain costs within their procedures for assessing, controlling, organizations. and mitigating such risks. Supplier/partner relationship Talent management As experienced supply chain managers Different organizations, even different retire, and organizations scale up to departments within the same meet growing demand in developing organization, can have different markets, talent acquisition, training, methods for measuring and and development is becoming communicating performance increasingly important. Supply chain expectations and results. Trust begins leaders need a thorough understanding when managers let go of internal biases of the key competencies required for and make a conscious choice to follow supply chain management roles, mutually agreed upon standards to specific job qualifications, methods for better understand current performance developing future talent and leaders, and opportunities for improvement. and the ability to efficiently source specific skill sets.
  • 21. Challenges in SCM industry
  • 22. How Big data can solve the problems?
  • 23. How Big data can solve the problems?
  • 24. How Big data can solve the problems?
  • 25. How Big data can solve the problems? Digital Path to Purchase. The work ecommerce. Amazon‘s work on that McCormick is doing on Digital Path to understanding demand insights of pantry Purchase is breakthrough thinking. I shopping is exciting. They are an early would start there. leader in Big Data techniques. I would have them at the top of my list. Listening. Text mining and ratings and Safe and Secure Supply Chains. The work review information at Bazaarvoice is a Big at Eli Lilly on product serialization of Data service. How could companies use pharmaceuticals has direct applicability of this data? How could it help in sensing where we are headed on food safety. Food early product failure? Only one out of ten and beverage companies need to learn companies that I talk to have ever heard from this early work in Big Pharma. of Bazaarvoice and the great work that . they are doing.
  • 26. How Big data can solve the problems? Supplier Sensing. The work at D&B on supplier sensing Supply Chain Visibility. Let’s face it, we have been is a great use of Big Data. I would include them in the talking about supply chain visibility and agile supply list and work with them on how consumer products chains for many years, but it has just been talk. The companies and retailers can sense supplier failure early use of rules-based ontologies and learning and use it to build stronger supplier relationships. We systems to redefine supply chain visibility at Conair is have talked about collaboration, but in reality, we have a new way to think about sensing supply chains. pushed costs and working capital back into the chain While early, it is a great case study on how to use Big increasing risk. The further back in the supply chain that Data techniques to solve a tough problem. we go and sense supplier health, the weaker the players and the greater the risk to the brand. The work at D&B is a great start to better understand this. Demand Insights. The work at Kraft on consumer Large-scale ERP. The race is on for global companies insights, or the work at General Mills on downstream to better serve emerging markets. These markets data are Big Data problems in the making. While both are fraught with disparate data that is often companies today are using more conventional incomplete. These large consumer products techniques, the size of the data is growing and insights companies are also the companies with BIG DATA can be gained on where we are headed. ERP systems. What are best practices for companies in the ERP Petabyte club? How does the data change? How does it affect maintenance and upgrade cycles? And the definition of business analytics?
  • 27. Migration to Big data for an SCM industry
  • 28. Migration to Big data for an SCM industry
  • 29. Migration to Big data for an SCM industry
  • 30. Migration to Big data for an SCM industry