LVO DA
Watch sales flow and data flow videos...
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Integration (scalability)....
All the different types and sources of data that are affecting the customers' need to grow their infrastructure vertically and/or horizontally can lead to creating additional complexities. This can stump your smartest customers.
Which of the following are Lenovo's comprehensive portfolio for data and analytics solutions? (Select all that apply.) -- ThinkAgile ThinkSystem TruScale xClarity Strategic Software Alliances
All... ThinkAgile ThinkSystem TruScale xClarity Strategic Software Alliances -- ThinkSystem, ThinkAgile, xClarity, TruScale, and strategic software alliances with SAP, VMware, Nutanix, Microsoft, and Red Hat are all Lenovo's comprehensive portfolio for data and analytics solutions.
Apache Hadoop -- Good for large scale batch processing Stores data on-disk Scales economically
Apache Spark -- Good for streaming analytics Utilizes in-memory computation for faster speed More expensive than Hadoop
SAP HANA is both a producer and a consumer of data. Producer: SAP HANA provides data requests for analytical and transactional purposes. Consumer: SAP HANA retrieves and aggregates data from various sources for storage and analysis.
Basically, there are two use cases for SAP HANA. Depending on the SAP environment, SAP HANA may be set up to support transactional or analytical applications. SAP HANA is typically found in IT landscapes supporting SAP business applications, but it can also be used in non-SAP environments. -- Intel Optane Persistent Memory does not lose data after a reboot. With the use of Intel Optane Persistent Memory, restart time for the SAP HANA in-memory database is reduced from hours to minutes. SAP certified appliances: SR950, SR860 V2, SR650.
Big data solutions typically involve one or more of the following types of workloads: Batch processing of big data sources at rest. Real-time processing of big data in motion. Interactive exploration of big data. Predictive analytics and machine learning.
Big data is used in nearly every business, large and small, to identify patterns and trends, answer questions, gain insights into customers, and tackle complex problems. Companies and organizations use the information for a multitude of reasons like growing their businesses, understanding customer decisions, enhancing research, making forecasts and targeting key audiences for advertising. -- Big Data Examples Personalized e-commerce shopping experiences Financial market modelling Compiling trillions of data points to speed up cancer research Media recommendations from streaming services like Spotify, Hulu and Netflix
Larger organizations are more likely to fall prey to data silos, for such reasons as they prefer to keep their data on-premises, and because decision making about new technologies is often slow. The ability to make fast decisions and quickly act on insights gained from the data is an advantage small businesses have over large organizations.
Choices - adding to the speed of evolution is the variety of available data technologies which organizations have to select.
Which two actions would you take upon discovering the business issue is not related to their data center? -- Mention they can always use more storage and make a pitch for Lenovo DE/DM. Present the value of Lenovo and remind them we have a variety of solutions addressing Big Data and analytics. Leave your card and graciously exit. Connect with the IT manager and learn as much as possible about their IT landscape and use of data. Take the opportunity to listen and learn more about their business operations.
Connect with the IT manager and learn as much as possible about their IT landscape and use of data. Take the opportunity to listen and learn more about their business operations.
You discover that your customer has a budget set aside, has sponsor support and has a business need which can be resolved by the implementation of a data center in the US. This is a clear opportunity. You are now on the customer's calendar for another meeting. What is your next step?
Contact a regional Tech Seller who has familiarity with the appropriate Lenovo Solution.
In this scenario Katrina uses a five step data flow model to trace the customer's end-to-end data data flow. Which selections accurately name 3 of the 5 steps? -- Data definition Data Ingest Data sorting Use of data Store data
Data Ingest Use of data Store data
Data Silos -- Organizations store all of this wonderful data they have captured in separate, disparate units, that have nothing to do with one another and therefore no insights can be gathered from this data because it simply isn't integrated.
Data Integration: Organizations face the challenge of integrating all these data sources to allow them to find value in their data. -- Data Accessibility The customer's level of difficulty reaching the data within the organization.
The five steps data flow model takes into account traditional and emerging technologies...
Data Source(s) Data Ingest Data Storage Data Analytics Use of reports and data insights obtained from analytics
Which three of the following are data producers?
Database Exports IoT devices Social Media
Databases store data in an organized structure of tables. People often refer to database applications, database management systems and databases under one umbrella term - Databases.
Database applications are computer programs that operate on a database. Database Management Systems (DBMS) control access to the database. Database applications work through a DBMS to gain access to the data.
An Oracle database server consists of a database and at least one database instance, commonly referred to as simply an instance. Because an instance and a database are so closely connected, the term Oracle database is sometimes used to refer to both instance and database. In the strictest sense the terms have the following meanings:
Database: a set of files, located on disk, that store data. These files can exist independently of a database instance. Database Instance: a set of memory structures that manage database files. The instance manages its associated data and serves the users of the database.
Data Architecture
Describes how data is collected, stored, transformed, distributed, and consumed. It includes the rules governing structured formats, such as databases and file systems, and the systems for connecting data with the business processes that consume it.
Analyze the data... (data flow model)
Do you have customized apps which use the data for operations or analysis?
Which three statements explain the needs of an IT director regarding data? -- Building a big data system that conforms with enterprise standards and meets core SLA requirements. Needs cost-effective, efficient solutions that perform impeccably all the time. Needs to know the ROI (return on investment) of the business. Ensuring that the big data framework and system scales to future demands and addresses the business needs. Ensuring that the big data framework and system will address security and performance concerns. Leverage the data to drive experiences that elevate the company's brand and business.
Ensuring that the big data framework and system will address security and performance concerns. Ensuring that the big data framework and system scales to future demands and addresses the business needs. Building a big data system that conforms with enterprise standards and meets core SLA requirements.
Business Operations: Focused on using Microsoft SQL Server purely for operational database needs, along the lines of classic online transaction processing (OLTP).
Enterprise Data Warehouse: Designed for data mining, analytics and continuous optimization of business strategy and operations, along the lines of classic online analytical processing (OLAP).
Lenovo supports industry-leading database applications including Microsoft SQL Server, SAP HANA, and Oracle Database.
For these types of opportunities you will want to contact your geo specific Services seller and provide them with the relevant information from the Record of Customer Engagement worksheet (attached in section above) that pertains to your database opportunity. You can reach them by contacting them directly or following your current geo specific guidelines. If you are unsure of who to contact, consult with your manager or CAM.
Information Architecture
Governs the processes and rules that convert data into useful information. For example, data architecture might feed raw daily advertising and sales data into information architecture systems, such as marketing dashboards, where it is integrated and analyzed to reveal relationships between ad spend and sales by channel and region.
Lenovo's solutions for Microsoft SQL Server benefit nearly any SMB, medium-sized organization, or large enterprise across verticals. For example:
Healthcare organizations can benefit from significant improvements in business transactions, such as extreme performance that meets SLA requirements. Media and broadcasting can benefit from high-density database consolidation, reducing data center costs. Retail can accelerate business analytics by combining Microsoft SQL Server and Lenovo high-end servers.
Common Apache software terms you may hear when talking about Big Data include: Spark - Interface for programming entire computer clusters and provides large scale data transformation, data analysis and real time access. Good for streaming analytics, more expensive than Hadoop. Hadoop - Falls under the category of a data lake. Hadoop manages storage (structured and unstructured data) and processing for big data applications running in clustered systems. Good for batch processing. Kafka- Stores, reads and analyzes streaming data. Often used in tandem with Hadoop, Storm and Spark Streaming.
Hive - Converts SQL queries to a format which can be used/understood by Hadoop. Hive enables users to interface with Hadoop using SQL. Flume - Software for collecting, aggregating and moving large amounts of log data. Flink - A pipelined runtime system that enables both batch and stream processing programs. Flink provides data source and connectors to programs such as Apache Kafka, and Hadoop Distributed File System.
Vertical scaling -- Customer is adding more CPU and RAM to a given machine to handle the demands of the database it is supporting. Relational databases are optimized for vertical scaling. In vertical scaling, the data resides on a single node and scaling is done through multi-core, in other words, spreading the load between the CPU and RAM resources of that machine.
Horizontal scaling -- Customer has to add more machines to the pool to handle the workload of the database that is running. Non-relational databases with their key-value stores are optimized for horizontal scaling. In a non-relational database world, horizontal scaling is often based on the partitioning of the data, in other words, each node contains only part of the data.
Influencer: IT -- Data analyst/architect IT Director Data scientist
How do I build a big data system that conforms with enterprise standards and meets core SLA requirements (internal and external customers)? I need to ensure that our big data framework and system scales to future demands and addresses our business needs (such as our myriad of data sources: ERP, social feeds, market and customer research, support inquiries, etc.). Is your architecture flexible enough to handle our unique data sources? How do you address my security and performance concerns?
What else would be helpful to discover about this customers source of data? -- What type of business decisions are made using your data? How is the data transported from IISC to the Reign data center? Is any of your data streamed? What repository do you use for the unstructured data? What data orchestration application do you use?
How is the data transported from IISC to the Reign data center? Is any of your data streamed?
High Availability
How much are your customers able to ensure that their data is able to withstand some sort of failure? For example, in a single server database, if the server goes down, the organization goes down. Having a data cluster, consisting of several servers working together, gives them multiple levels of redundancy. A distributed database also has assignment failover so when a node performing a specific task goes down, that task is automatically transferred to a working node. Writing a transaction to a local disk is a lot faster than having to shuffle it across a distributed network.
Sponsor: Line Of Business (LOB) -- VP of Sales, Marketing, CMO
I need the right data and insights available at every moment, from anywhere to drive fast, informed decisions. Keywords: always available, anytime, anywhere, actionable insights. I need cost-effective, efficient solutions that perform impeccably all the time
Oracle Real Application Clusters (RAC) is an option to Oracle's Database Enterprise Edition. Oracle RAC is a cluster database with a shared cache architecture. Oracle Real Application Clusters provide high availability by eliminating an individual database server as a single point of failure.
In a clustered server environment, the database itself is shared across a pool of servers, which means that if any server in the server pool fails, the database continues to run on surviving servers. Oracle RAC enables businesses to continue processing database workloads in the event of a server failure, it also helps to further reduce costs of downtime by reducing the amount of time databases are taken offline for planned maintenance operations.
In the big data and analytics context, the purpose of a greenfield deployment is when a customer wants to collect data for a new project or from a new environment.
In the big data and analytics context, 90% of the cases are brownfield deployments. We are looking at existing data platforms for modernizing and create a single source of truth, taking the data from multiple independent databases, put it in a data lake and formatting it in a way to be consumed by artificial Intelligence. -- You are more likely to find brownfield deployments than greenfield.
SAP HANA is an exceptionally versatile, fast, feature rich and powerful in-memory relational database which provides an excellent platform for analytics. An in-memory database is one that primarily relies on main memory for storage, versus disk storage.
In-memory technology accelerates data access because it allows SAP HANA to process data from within RAM as opposed to reading it from a hard drive. Reaching out to the hard drive for data retrieval is significantly slower than accessing the memory. -- 2027 marks SAP's EOS (End of Support) for all databases other than SAP HANA. All SAP Business Suite customers will need to migrate their applications to S/4 HANA which is optimized for the HANA database.
When we are talking about big data and analytics, many people can have an impact on the decision-making process, but the main roles are:
Influencer: IT Sponsor: C-Suite (CxO) Sponsor: Line Of Business (LOB)
Which statements are true for an RFT document? -- Is used when purchaser has clearly defined criteria or specification. Is used when you know you have a problem but don't know how you want to solve it. Is similar to an RFI document. Is an opportunity for potential suppliers to submit an offer to supply goods or services against a detailed tender. Purchaser is not necessarily committed to buying.
Is used when purchaser has clearly defined criteria or specification. Is an opportunity for potential suppliers to submit an offer to supply goods or services against a detailed tender.
In A.C.I.D acronym, identify the function each letter ensures. -- Atomicity: If the deposit transaction fails, the withdrawal operation won't happen. Consistency: Illegal transactions can't corrupt the database.
Isolation: All transactions are processed securely and independently. Durability: The data won't be lost even if the system crashes.
Microsoft SQL Server and Oracle Database are two of the most popular, time-tested options for relational database management in large enterprises. -- Microsoft SQL Server is a relational database management system (RDBMS) developed by Microsoft that supports a wide variety of applications - from transaction processing to business intelligence to analytics.
It uses a common set of tools to deploy and manage databases for in-house and cloud environments. As the name suggests, SQL Server is built on top of structured query language (SQL) - the standard language for relational database management systems. Database administrators and IT professionals use SQL to manage and search databases.
The MS SQL Server DWFT program is a joint effort between Microsoft and hardware partners. The goal is to provide enterprise customers with proven and recommended system architectures which support workloads with reduced risk, cost and less complexity.
Lenovo Database Solutions for Microsoft SQL Server Data Warehouse Fast Track (DWFT) improve time-to-value for data warehousing needs with a new scalable architecture. They use high performance Lenovo ThinkSystem servers combined with ThinkSystem Hot Swap SSDs to solve SQL database warehouse needs up to 200 TB in size. -- These solutions are OLAP only offerings; OLTP offerings are not part of DWFT. The Microsoft Data Warehouse Fast Track (DWFT) for SQL Server Program is designed to reduce the time necessary for enterprise leaders to build configurations that solve data warehousing issues.
Cloudera is a data platform that helps businesses manage and secure their end-to-end data lifecycle - collecting, enriching, analyzing, experimenting and predicting with their data - to drive actionable insights and data-driven decision making. This is commonly called the CDP (Cloudera Data Platform). CDP provides an integrated data platform that creates agility along lines-of-business while facilitating efficiency and security within IT, enabling the entire organization to be more productive.
Lenovo partners with Cloudera to provide a predefined and optimized hardware infrastructure for Cloudera Data Platform, a distribution of Apache Hadoop and Apache Spark with enterprise-ready capabilities from Cloudera. Lenovo provides solutions for compute-intensive, storage-intensive, streaming data, and/or private/hybrid cloud environments.
For decades, Oracle has had better scalability and security than SQL Server, making it better suited for large enterprises. In addition, SQL Server was available only for Windows until SQL Server 2017, leaving Linux users out in the cold. This perception has evolved in recent years. Both Oracle and SQL Server have released mature enterprise and standard versions of their platform, for both Windows and Linux.
Most analysts would agree that Oracle still has a slight edge over Microsoft in terms of both core database features and cutting-edge functionality. However, these extra capabilities have a downside. Oracle is typically more complex to manage, has a higher learning curve and costs more to maintain.
The Elements of Data Strategy: Offense Improve competitive position and customer satisfaction and increase revenue and profitability.
Optimize data analytics, modeling, visualization, transformation, and enrichment. Integrate disparate customer and market data to support managerial decision making through, for instance, interactive dashboards.
The Elements of Data Strategy: Defense Ensure data security, privacy, integrity, quality, governance, and regulatory compliance (rules governing data privacy and the integrity of financial reports).
Optimize data extraction, standardization, storage, and governing authoritative data sources, such as fundamental customer and supplier information or sales data.
Oracle Database is available on-prem, on-cloud or as hybrid cloud installation to provide a range of industry-leading solutions that meet the data management requirements from small and medium sized businesses to large global enterprises.
Oracle database deployments are used in everything from departmental databases to business-critical workloads, including enterprise resource planning, customer relationship management and business intelligence. These databases can be highly scalable and highly available to allow for 24x7x365 continuous operation with the Real Application Clusters (RAC) option. The current Oracle database product is the Oracle Autonomous Database.
The platform versatility may be important to some customers. As a Microsoft product, SQL Server has traditionally only been available for the Windows operating system. However, beginning with SQL Server 2017, the platform is now available on Linux as well and can run as a Docker image. Note that if you want to use an earlier version of SQL Server, you will have to use it with Windows.
Oracle, meanwhile, has a long history of supporting both Windows and Linux. Oracle Database is also available for other Unix-based operating systems such as Oracle Solaris, IBM AIX and HP-UX. However, neither Oracle nor SQL Server supports Mac OS X.
Private sector The source of funds for the project are often from the company's central financing system, which may be a combination of borrowing from financial institutions, retained profits, financial reserves and progress, or down payments expected to be made by the client.
Other sources of funds may be based on direct funding of the project; thus this can be done by the issue of commercial paper, bank loans, public debt offerings, private placements in the market, syndicated commercial long-terms loans, and government entity loans, to name just a few.
Public Sector The budget may be the grant or bond.
Public sectors include public goods and governmental services such as the military, law enforcement, infrastructure, public transit, public education, along with health care and those working for the government itself, such as elected officials.
RFI = request for information ROI = registration of interest
RFP = request for proposal RFT = request for tender RFQ = request for quotation
Which of the following are common business problems for databases and Big Data? (Choose three answers.) -- Budget Surplus Resource Utilization Licensing Performance Scalability
Resource Utilization Performance Scalability
Speed: It relates to data retrieval, lookup, and reporting. How quick is the response to the request? Data Safety and Integrity: The customer expects the data that is processed will be intact and nothing is lost. Does it satisfy the Industry A.C.I.D. test?
Resource Utilization: Customers often make false assumptions that if their relational or non-relational databases run on the best hardware available to them then it would behave, accordingly. Today, with the prevalence of containers and VM deployment, that isn't the case. To keep up performance in the face of finite compute and memory resources and the need to handle larger amounts of more complex data, customers must get 100 percent out of the resources it has for every nanosecond of the day.
Lenovo supports industry-leading database applications including: -- IBM Cloud Databases SAP HANA Microsoft SQL Server PostgreSQL
SAP HANA Microsoft SQL Server
Which problem does Lenovo answer with the servers that provide highly reliable and flexible foundations for the customers' business solutions so they can unlock the value of their data and deliver insights faster and drive faster time to value? -- Scalability Security Protection Management
Scalability -- Lenovo answers the scalability problem with the servers that provide highly reliable and flexible foundations for the customers' business solutions so they can unlock the value of their data and deliver insights faster and drive faster time to value.
Single Source of Truth (SSoT)
Single Source of Truth (SSoT) data, as HBR (Harvard Busines Review) defines it, relies on one unchallengeable source within an organization to deliver all the crucial data needed to run it's business. Things like customer details, supplier details and product information should come from a SSoT. When we are talking about SSoT we are talking about the veracity of data. The SSoT works at the data level. An SSoT representing the veracity of data, is the source from which multiple versions of the truth are developed.
The performance expectations will be determined by the following four pillars....
Speed Data Safety and Integrity Resource Utilization High Availability
Step 1: Research Step 2: Identify the need
Step 3: Get agreement (After meeting with your customer and gathering information, populate Record of Customer Engagement document). Step 4: Secure next meeting with Lenovo Technical Seller
Pick the list of the top customer reasons to move to big data and analytics. -- Reduced costs, flexibility, no need for a backup plan. Securing the workplace, moving desktops to cloud, mobility. Increase availability, improve collaboration, increase profit. Storing volumes of data is problematic, poor data ingestion rate, faster and better decision making.
Storing volumes of data is problematic, poor data ingestion rate, faster and better decision making.
Which four big data use cases are for manufacturing? -- Supply chain optimization Defect tracking Marketing campaign optimization Increased collaboration Root cause analysis Server consolidation
Supply chain optimization Defect tracking Root cause analysis Increased collaboration
Target Customers for Lenovo Data and Analytics Solutions...
Telecom Manufacturing Healthcare/pharma Finance Retail
Variety
The different types of data the organization is collecting to gain business insight. Unstructured data like videos, photos, music, GPS sensor signals and billions of social media posts or text messages are just a few examples of the variety of data. It's estimated that this data makes up about 80% of what companies store.
Velocity
The speed at which the data is coming into the organization. How fast the data is coming in and being ingested. Timeliness, or latency, is a velocity issue.
During the big data planning/refresh meeting, sales rep talks through her diagrams and highlights a few points. The business gap/agreed reason for change. The stakeholders, their positions and relationship to the data center.
The state of their current hardware (upgrades, software versions etc.). Their preferred software vendor. Size and general skill level of the IT team. They work with an SI which will be invited to the meeting.
Lenovo's ThinkShield is a portfolio of security features and products based on the latest technology innovations. It provides the strongest foundation of defense to help your customer prevent, detect, and recover from security attacks. Lenovo believes that the foundation on which they build their business should be solid and ThinkShield allows us to do this.
ThinkShield is a transparent and comprehensive approach to security that extends to all dimensions of our datacenter products - from development, to supply chain, and through the full lifecycle of the device. The data center group at Lenovo provides this secure foundation in three main ways: • A secure business process • A secure product design • A secure supply chain
Lenovo offers MS SQL Server Database solutions on ThinkSystem and ThinkAgile. ThinkSystem servers supporting MS SQL Server include:
ThinkSystem SE350 ThinkSystem SR630 ThinkSystem SR650 MX, HX, SXM
SQL Server licenses are significantly cheaper than Oracle. While the sticker price may be lower on SQL Server, you should also consider the total cost of ownership over the lifetime of the database.
This includes considerations such as support, maintenance, and productivity during day-to-day use. Like SQL Server, Oracle Database has been innovating in recent years to keep up with customers' demands for processing big data. -- Language • Both Oracle and SQL Server come with their own dialect of the SQL language • Oracle uses PL/SQL (Procedural Language/SQL) • SQL Server uses T‐SQL (Transact‐SQL) • PL/SQL and T‐SQL each have their own distinct features, abilities, and syntax.
You have probably seen and used the Record of Customer Engagement document included in the Database Playbook....
This tool/document provides a guide to the basic information you should gather and provide to the Lenovo expert on SAP HANA, Database or Big Data opportunities. After meeting with your customer and gathering information, populate this form and send to your Lenovo expert as you engage them.
True or False: Cloudera is one of Lenovo's partners in Big Data.
True
True or False: Big Data architecture is a combination of various technologies working together to provide a specific solution for a customer's given business problem.
True
Data can be structured or unstructured. -- Structured data is clearly defined data types: numbers, names, dates, credit card numbers - transactional information. Structured data is easily organized in rows and columns, such as in spreadsheets and conventional databases.
Unstructured data is - unstructured. It doesn't have any predetermined form. Unstructured data flows continuously rather than being captured as discrete transactions and includes things like emails, text messages, audio and video files, tweets, satellite and surveillance images.
Small 5 Vs
Value Veracity Viscosity Variability Virality
Viscosity: How easily does the customer's data flow within the organization
Variability: The organization challenge to handle the frequency of change with their data -- Virality: The speed the information spreads through the organization
What are the big 3 Vs of data?
Variety Velocity Volume
Variability is different from variety. A coffee shop may offer 6 different blends of coffee, but if you get the same blend every day and it tastes different every day, that is variability. The same is true of data, if the meaning is constantly changing it can have a huge impact on your data homogenization.
Veracity is all about making sure the data is accurate, which requires processes to keep the bad data from accumulating in your systems. The simplest example is contacts that enter your marketing automation system with false names and inaccurate contact information. How many times have you seen Mickey Mouse in your database? It's the classic "garbage in, garbage out" challenge. Value is the importance of data. How important is the big data to the organization.
Value: How the organization generates their insight from the huge lump of data they have collected
Veracity: The customer's accuracy of their data. The organization's plan for a single source of truth
Unstructured data like videos, photos, music, GPS sensor signals and billions of social media posts or text messages are just a few examples of the variety of data. It's estimated that this data makes up about 80% of what companies store. While volume, velocity, and variety are referred to as the big V's, don't forget there are some smaller V's that are discussed in the industry, value, veracity, variability, viscosity, and virality are all relevant to any big data plan.
Viscosity measures the resistance to flow in the volume of data. This resistance can come from different data sources, friction from integration flow rates and processing required to turn the data into insight. Virality describes how quickly information gets dispersed across people to people (P2P) networks. Virality measures how quickly data is spread and shared to each unique node. Time is a determinant factor along with rate of spread.
Big 3 Vs -- Volume Variety Velocity
Volume: The amount of structured and unstructured data the organization is under stress to store for accurate analysis. Traditional databases struggle with handling such big volumes of data on a single server and can also be plagued by slow response times.
Which two questions below help to discover your customer's business data flow? -- What are the sources of your data? What type of servers do you have in your data center? How is your data center financed? Have you considered big data solutions? Do you stream any data?
What are the sources of your data? Do you stream any data?
Use of the data... (data flow model)
What decisions are made with your data? Who are the end users of it and how do they use it?
When talking to the COO which two questions would help you find out more about the company's use of data? -- What decisions are you making with your data? What would you like your data to do for you? Are your workloads virtualized? Do you use the Cloud for storing data?
What decisions are you making with your data? What would you like your data to do for you?
Information Collected with Record of Customer Engagement Form... Biggest challenges? Budget? Are you using SAP?
What decisions do you make with your data? What is your current data architecture? Where is your data located? Where is your data coming from? How do you aggregate and consolidate data today? -- The category of your opportunity, Database, Big Data or SAP HANA, will determine who you will need to contact to assist you with the opportunity. For SAP, use CoC.
It is important to gather the budget information before reaching out to a solution specialist, as this information determines the timeline scope and may exclude options that are too expensive from the beginning of the discussion.
What is their budget? Do they have one? What is their budget cycle? How do they fund projects?
Which discovery question you should ask if you hear from a customer: "I'm struggling to find value in my data"? -- Is your organization planning to use cloud? What type of data are you collecting? Are you using storage virtualization? Are you aware of the data warehouse work Lenovo has done with Microsoft?
What type of data are you collecting?
What other questions would explore the stakeholder's perspective on what the data should do for them?
What type of insights would you like to achieve from this data? This question will help to uncover how they plan to use the data. -- How do you see integrating the weather data into your business? This question steps further into the conversation of how the weather data would align with their current data. -- Which category of Lenovo solutions would most likely help this customer? Lenovo Solutions for Big Data
Data store... (data flow model)
What type of repositories are you using for your unstructured data?
Sponsor: C-Suite (CxO) -- CIO, CTO, CDO, VP of Infrastructure
What's my ROI? Does this solution improve the decision-making capabilities of my staff and customers? Confidence/risk-averse: If something goes wrong, I don't want to be held responsible. Can you ensure that I'm working with trustworthy partners who will be accountable? Is this solution robust enough to capture all the data I need to innovate? How does it help me create value from data? How can I leverage the data to drive experiences that elevate our brand and business?
Ingest data... (data flow model)
When the data enters your data center, how is it transformed and directed?
Multiple Versions of Truth (MVoTs)
When we talk about Multiple Versions of Truth (MVoT) we're not talking about alternative facts, HBR tells us that we're simply talking about turning this raw SSoT data into information. Each department of the business will take this SSoT data and imbue it with relevance and purpose by putting it in some form of context. MVoTs support the management of information.
You also need perspective from the Director of IT. Which two questions would help you find out more about her data needs? -- Where is your data stored, and would you consider data storage in the cloud? How much has your volume of data increased this past year? How does finance use the data? What company decisions are made with the data? How does supply chain use the information from the dairy app?
Where is your data stored, and would you consider data storage in the cloud? How much has your volume of data increased this past year?
Which of the following would help uncover details of their IT landscape? (pick two) -- Let's talk about storage. Lenovo offers some very dependable storage solutions. Which databases do you use? Do you use any industry specific applications? It sounds like your company is going through some growing pains and IT needs to catch up. Have you considered Big Data solutions?
Which databases do you use? Do you use any industry specific applications?
Lenovo engineered solutions for big data will provide your customer with a well-defined scope, including a complete listing of requirements. Contact your geo specific Services seller and provide them with the relevant information from the Record of Customer Engagement worksheet (attached in section above) that pertains to your big data opportunity.
You can reach them by contacting them directly or following your current geo specific guidelines. If you are unsure who to contact consult with your manager or CAM.
Which of the following questions would be best to continue to connect with the COO and gather the information you need? -- Do you contract the cows through local farmers? I understand you are the new "kid on the block", but your quality far surpasses the standard dairies. You have become so popular so quickly, sounds like you are concerned about keeping up with the demand? How do you predict what the market will be for which flavors?
You have become so popular so quickly, sounds like you are concerned about keeping up with the demand?
Oracle Database (commonly referred to as Oracle DBMS or simply as Oracle) is...
a multi-model database management system commonly used for running online transaction processing (OLTP), data warehousing (DW) and mixed (OLTP & DW) database workloads.
Like other RDBMS technologies, SQL Server is primarily built around...
a row-based table structure that connects related data elements in different tables to one another, avoiding the need to redundantly store data in multiple places within a database. The relational model also provides referential integrity and other integrity constraints to maintain data accuracy.
A data consumer is a system or tool that uses data. Examples of data consumers are...
analytic engines, AI, machine learning, operational databases and humans. It is important to note that a single system can be both a consumer and a producer of data.
For SAP HANA opportunities...
contact the SAP Center of Competence via email, [email protected] with a completed Record of Customer Engagement worksheet, making sure to fill in the SAP questions and attach it to an email. It is that simple.
Data Warehouses are...
databases that consolidate structured data from a variety of different databases into one place, enabling analysis and reporting on this varied amount of data. -- Structured, Processed. Expensive for large data volumes. Less agile, fixed configuration. Mature security. Users: Business Professionals.
Engage with your Lenovo ISG Specialist when you have __________ and gathered enough information to feel confident you have a data and analytics opportunity. -- had at least 2 meetings had at least 1 meeting had at least 4 meetings had at least 5 meetings
had at least 1 meeting
NoSQL...
languages are used to query non-relational databases.
Databases have continued to evolve and two of the most common types of databases today are relational (or SQL) and non-relational (or NoSQL) databases. -- Relational databases...
organize data into tables which are linked, or related, by common data. Relational databases are sometimes referred to as SQL databases.
Data Lakes are...
repositories that enable storage of both structured and unstructured data. -- Structured/Semi-structured/Unstructured, Raw. Designed for low-cost storage. Highly agile, configure and reconfigure as needed. Maturing security. Users: Data Scientists, et al.
What is the correct email address to contact the SAP Center of Competency? -- [email protected] [email protected] [email protected] [email protected]
[email protected] -- It enables customers to receive insightful information around their SAP Implementations. • Sizing and Architecture guidelines • Lenovo recommendations for SAP Landscapes • Architecture advice on all SAP applications • Guidance on solution features
SQL...
stands for Structured Query Language, the standard language used to program or query a relational database management system (RDBMS).
Non-relational databases...
store data in non-tabular formats and are considered more flexible than traditional relational databases. Non-relational databases are sometimes referred to as NoSQL databases.
The Record of Customer Engagement, included in this course, serves as a guide to... -- documenting customer information in MS Dynamics. sizing an SAP HANA opportunity. the basic information you should gather and provide to the specialist. moving a VDI opportunity forward.
the basic information you should gather and provide to the specialist.
