Salesforce Salesforce Consultant Analytics-Con-201

近年に、Salesforce Analytics-Con-201 「Salesforce Certified CRM Analytics and Einstein Discovery Consultant」 認定試験は重要なコンピュータ能力認定試験になっています。Salesforce 国際認証資格取得者になったら、求職がもっと易く、高給料も当たり前です！

でも、どうやって簡単的にスムーズに Salesforce Analytics-Con-201 試験を合格しますか、JapanCert会社だ！助けるよ。

JapanCertは国際ＩＴ認証試験資料集を提供するＷｅｂです。JapanCert会社は最良最新の試験資料の資源です、JapanCert会社が提供する Salesforce 認定資格試験問題集は豊富な経験のＩＴ専家に過去試験より一生懸命に研究する出題傾向のです。

問題集の正確率は９９％になって、１００％に合格できて、安心に試験しましょう。

我社の Salesforce Analytics-Con-201 は今では最新の問題集で、試験範囲を１００％網羅して一番な試験助手になります。20時間から３０時間ぐらいかかるなら、内容を覚えるだけいいです。

問題集がいつも最新の状態を持つために、Salesforce Analytics-Con-201 認証問題集を購入いただくお客様が一年の更新サービスを無料に提供します。もしこちらで提供する問題集を使用して未合格したら、Prometric或いはVUE発行する成績を確認後、全額に返金します、絶対にお金を無駄にならない。

JapanCert試験問題集はPDF版とソフト版を提供します。PDF版は印刷されることができます、ソフト版はどのパソコンでも使われることもできます。

JapanCertの試験資料を買うかどうかと迷ったら、Salesforce Analytics-Con-201 「Salesforce Certified CRM Analytics and Einstein Discovery Consultant」 試験の部分問題と回答を無料にダウンロードして試用する後、決めて信じてくれます。早ければJapanCertを信じてくれて、早く成功になっています。

簡単で便利な購入方法：ご購入を完了するためにわずか2つのステップが必要です。弊社は最速のスピードでお客様のメールボックスに製品をお送りします。あなたはただ電子メールの添付ファイルをダウンロードする必要があります。

Analytics-Con-201オンライン版は Windows / Mac / Android / iOS 対応です。

Salesforce Certified CRM Analytics and Einstein Discovery Consultant 認定 Analytics-Con-201 試験問題:

1. Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.
How should CK achieve this?

A) An SAQL query with a timeseries statement specifying Opportunity Name as the partition and Y-M-W as the Date Cols
B) An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W as the Date Cols
C) An SAQL query with @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols

2. A team of CRM Analytics developers has been working on an existing recipe to add new derived fields. The edited version has been failing ever since, and management is requesting that the dashboard show refreshed data while they work on the edits.
How can the developers add new fields while keeping the dataset refreshed?

A) Refresh the dataset after working hours to avoid the edited version from failing.
B) Clone the existing recipe to add fields and roll back the original recipe to the last working version.
C) A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.

3. The CRM Analytics consultant at Cloud Kicks is asked to a dashboard displaying Opportunities data on the account's record page. The dashboard should display only opportunity data related to the current account viewed.
How should the consultant accomplish this?

A) Create the dashboard, insert in the account's record page, and apply a filter based on the opportunity's Id field.
B) Create a dashboard, clone it and filter It for each account record, and embed them into the account's record pages accordingly.
C) Create the dashboard, insert in the account's record page, and apply a filter based on the account's Id field.

4. The CRM Analytics consultant at AW Computing is designing dashboard. They want to add a rate between two metrics and display it in a new chart. They are finding that the new chart seems to prejudice the design of other charts.
What should the consultant do to resolve this?

A) Create a component with the rate chart and insert it in one of the tooltips.
B) Adjust the dashboard widgets to accommodate the rate chart.
C) Clone the dashboard and replace one of the charts with the new rate chart.

5. A consultant is preparing a dataset to predict customer lifetime value and is collecting data from a questionnaire that asks for demographic information. A very small number of respondents fill in the Income box, but the consultant thinks that it is an informative column even though it only represents 1% of respondents.
What should the consultant do?

A) Fill in the missing data with an average of all incomes.
B) Apply the predict missing values transformation in recipe nodes.
C) Drop the field as it will be difficult to get future respondents.

質問と回答：