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NEW QUESTION: 1
Case Study 1 - Flowlogistic
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
* 10 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.
Flowlogistic's CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they've purchased a visualization tool to simplify the creation of BigQuery reports. However, they've been overwhelmed by all the data in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?
A. Create an additional table with only the necessary columns.
B. Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.
C. Export the data into a Google Sheet for virtualization.
D. Create a view on the table to present to the virtualization tool.
Answer: D

NEW QUESTION: 2
You are the network consultant from The Tech LTD. You need to explain to customers two ways to support load balancing across more than two WAEs, they are? (Choose two.)
A. GSSP
B. CIFS
C. Cisco ACE
D. WCCPV2
Answer: C,D

NEW QUESTION: 3
Given:
1.public class Threads2 implements Runnable {
2.3.
public void run() {
4.System.out.println("run.");
5.throw new RuntimeException("Problem");
6.}
7.public static void main(String[] args) {
8.Thread t = new Thread(new Threads2());
9.t.start();
10.System.out.println("End of method.");
11.}
12.}
Which two can be results? (Choose two.)
A. run.
java.lang.RuntimeException: Problem
B. java.lang.RuntimeException: Problem
C. run.
java.lang.RuntimeException: Problem
End of method.
D. End of method.
run.
java.lang.RuntimeException: Problem
E. End of method.
java.lang.RuntimeException: Problem
Answer: C,D

NEW QUESTION: 4
概要
アプリケーション概要
Contoso、Ltd.は、エンタープライズリソースプランニング(ERP)アプリケーションの開発者です。
ContosoはERPアプリケーションの新しいバージョンを設計しています。以前のバージョンのERPアプリケーションはSQL Server 2008 R2を使用していました。
新しいバージョンはSQL Server 2014を使用します。
ERPアプリケーションは、サプライヤデータをロードするためのインポートプロセスに依存しています。インポートプロセスは、何千もの行を同時に更新し、データベースへの排他的アクセスを必要とし、毎日実行されます。
ERPアプリケーションの予期しない動作を報告するサポートコールがいくつかあります。呼び出しを分析した後、ユーザーはデータベース内のテーブルに直接変更を加えたと結論付けました。
テーブル
現在のデータベーススキーマには、OrderDetailsという名前のテーブルが含まれています。
OrderDetailsテーブルには、各注文書に対して販売された商品に関する情報が含まれています。 OrderDetailsは、購買発注の各製品に適用される製品ID、数量、および割引を格納します。
製品の価格はProductsという名前のテーブルに格納されています。 Productsテーブルは、SQL_Latin1_General_CP1_CI_AS照合順序を使用して定義されました。
ProductNameという列が、varcharデータ型を使用して作成されました。データベースにはOrdersという名前のテーブルが含まれています。
注文には、過去12か月間のすべての注文書が含まれています。 12か月以上前の注文書はOrdersOldという名前のテーブルに格納されています。
以前のバージョンのERPアプリケーションは、テーブルレベルのセキュリティに依存していました。
ストアドプロシージャ
データベースの現在のバージョンには、2つのテーブルを変更するストアドプロシージャが含まれています。以下に、2つのストアドプロシージャの関連部分を示します。

顧客の問題
インストールの問題
現在のバージョンのERPアプリケーションでは、いくつかのSQL Serverログインが正しく機能するように設定されている必要があります。ほとんどの顧客はERPアプリケーションを複数の場所に設定しており、ログインを複数回作成する必要があります。
インデックスの断片化の問題
顧客は、クラスタ化インデックスが断片化していることが多いことを発見しました。この問題を解決するために、顧客はより頻繁にインデックスを最適化します。断片化の影響を受けるすべてのテーブルには、クラスタ化インデックスキーとして使用される次の列があります。

バックアップの問題
大量の過去の注文書データを持っている顧客は、バックアップ時間が許容できないと報告しています。
検索の問題
ユーザーは、製品名を検索すると、検索文字列にアクセントが含まれていない限り、検索結果にアクセントを含む製品名が除外されると報告しています。
欠落データの問題
顧客は、商品テーブルで価格を変更すると、以前の注文で商品が販売された価格を取得できないと報告しています。
クエリパフォーマンスの問題
顧客は、クエリのパフォーマンスが急速に低下すると報告しています。さらに、顧客は、SQL Serverがメンテナンスタスクを実行するときにユーザーがクエリを実行できないと報告しています。インポートの問題データベース管理者は、毎月のインポート処理中に、サプライヤデータにアクセスできないと報告したユーザーから多くのサポート要請を受けます。データベース管理者は、データのインポートに必要な時間を短縮したいと考えています。
設計要件
ファイルストレージ要件
ERPデータベースには、2 MBを超えるスキャン文書が保存されています。これらのファイルはERPアプリケーションを介してのみアクセスする必要があります。ファイルアクセスは、可能な限り最高の読み書きパフォーマンスを持つ必要があります。
データ復旧の要件
インポートプロセスが失敗した場合は、データベースをすぐに以前の状態に戻す必要があります。
セキュリティ要件
基礎となるテーブルに直接アクセスすることなく、ERPアプリケーション内で機能を実行する機能をユーザに提供する必要があります。
同時実行要件
Sales.ProdとSales.Proc2の実行時にデッドロックが発生する可能性を減らす必要があります。
バックアップの問題に対処するソリューションを推奨する必要があります。
解決策は開発努力の量を最小にしなければなりません。
あなたは推薦に何を含めるべきですか?
A. インデックス
B. 表分割
C. ファイルグループ
D. インデックス付きビュー
Answer: C
Explanation:
Explanation
- Backup Issues
Customers who have large amounts of historical purchase order data report that backup time is unacceptable.
- For very large databases (and by that, I mean, at least 500gb, but more like 5-10tb or more), it can become too expensive to regularly run a straight full backup.
So, where needed, you can choose to backup smaller pieces of the database by choosing to back up one of the files or file groups that make up a database.


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