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NEW QUESTION: 1
Which is a purpose of the Consultancy and Performance Management role?
A. Assists with budget control
B. Provides benefits realization support
C. Identifies, monitors and resolves issues
D. Creates, maintains and distributes good practice
Answer: D

NEW QUESTION: 2
Which of the following tools can be used for passive OS fingerprinting?
A. nmap
B. tracert
C. ping
D. tcpdump
Answer: D
Explanation:
Explanation
The passive operating system fingerprinting is a feature built into both the pf and tcpdump tools.
References:
http://geek00l.blogspot.se/2007/04/tcpdump-privilege-dropping-passive-os.html

NEW QUESTION: 3
データベースのRMANイメージ・コピーを作成する場合、どちらの記述が正しいですか？ （2つを選択してください）
A. これらはすべて、データファイル内の未使用ブロックを使用して構成されています。
B. ディスクに書き込むことができます。
C. データベースがMOUNT状態のときにのみ作成できます。
D. データベースがNOARCHIVELOGモードで実行されている場合のみ可能です。
E. データベースがARCHIVELOGモードで実行されている場合にのみ作成できます。
Answer: A,B
Explanation:
Explanation
An image copy can be written only to disk.
An image copy is the same as datafiles. The disadvantage of image copy backup mode is that it occupies much space and does not skip unused data blocks.
http://www.dba-oracle.com/t_rman_10_image_copies.htm

NEW QUESTION: 4
Your company's customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations. What should you do?
A. Use an ETL tool to load the data from MySQL into Google BigQuery.
B. Add a node to the MySQL cluster and build an OLAP cube there.
C. Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.
D. Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.
Answer: D
Explanation:
Topic 2, Flowlogistic Case Study
Company Overview
Flowlogistic is a leading logistics and supply chain provider. They help businesses throughout the world manage their resources and transport them to their final destination. The company has grown rapidly, expanding their offerings to include rail, truck, aircraft, and oceanic shipping.
Company Background
The company started as a regional trucking company, and then expanded into other logistics market. Because they have not updated their infrastructure, managing and tracking orders and shipments has become a bottleneck. To improve operations, Flowlogistic developed proprietary technology for tracking shipments in real time at the parcel level. However, they are unable to deploy it because their technology stack, based on Apache Kafka, cannot support the processing volume. In addition, Flowlogistic wants to further analyze their orders and shipments to determine how best to deploy their resources.
Solution Concept
Flowlogistic wants to implement two concepts using the cloud:
* Use their proprietary technology in a real-time inventory-tracking system that indicates the location of their loads
* Perform analytics on all their orders and shipment logs, which contain both structured and unstructured data, to determine how best to deploy resources, which markets to expand info. They also want to use predictive analytics to learn earlier when a shipment will be delayed.
Existing Technical Environment
Flowlogistic architecture resides in a single data center:
* Databases
* 8 physical servers in 2 clusters
* SQL Server - user data, inventory, static data
* 3 physical servers
* Cassandra - metadata, tracking messages
10 Kafka servers - tracking message aggregation and batch insert
* Application servers - customer front end, middleware for order/customs
* 60 virtual machines across 20 physical servers
* Tomcat - Java services
* Nginx - static content
* Batch servers
Storage appliances
* iSCSI for virtual machine (VM) hosts
* Fibre Channel storage area network (FC SAN) - SQL server storage
* Network-attached storage (NAS) image storage, logs, backups
* Apache Hadoop /Spark servers
* Core Data Lake
* Data analysis workloads
* 20 miscellaneous servers
* Jenkins, monitoring, bastion hosts,
Business Requirements
* Build a reliable and reproducible environment with scaled panty of production.
* Aggregate data in a centralized Data Lake for analysis
* Use historical data to perform predictive analytics on future shipments
* Accurately track every shipment worldwide using proprietary technology
* Improve business agility and speed of innovation through rapid provisioning of new resources
* Analyze and optimize architecture for performance in the cloud
* Migrate fully to the cloud if all other requirements are met
Technical Requirements
* Handle both streaming and batch data
* Migrate existing Hadoop workloads
* Ensure architecture is scalable and elastic to meet the changing demands of the company.
* Use managed services whenever possible
* Encrypt data flight and at rest
* Connect a VPN between the production data center and cloud environment SEO Statement We have grown so quickly that our inability to upgrade our infrastructure is really hampering further growth and efficiency. We are efficient at moving shipments around the world, but we are inefficient at moving data around.
We need to organize our information so we can more easily understand where our customers are and what they are shipping.
CTO Statement
IT has never been a priority for us, so as our data has grown, we have not invested enough in our technology. I have a good staff to manage IT, but they are so busy managing our infrastructure that I cannot get them to do the things that really matter, such as organizing our data, building the analytics, and figuring out how to implement the CFO' s tracking technology.
CFO Statement
Part of our competitive advantage is that we penalize ourselves for late shipments and deliveries. Knowing where out shipments are at all times has a direct correlation to our bottom line and profitability. Additionally, I don't want to commit capital to building out a server environment.