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DAA-C01최신인증시험공부자료 & DAA-C01최신버전시험덤프

Itexamdump의 제품들은 모두 우리만의 거대한IT업계엘리트들로 이루어진 그룹 즉 관련업계예서 권위가 있는 전문가들이 자기만의 지식과 지금까지의 경험으로 최고의 IT인증관련자료를 만들어냅니다. Itexamdump의 문제와 답은 정확도 적중률이 아주 높습니다. 우리의 덤프로 완벽한Snowflake인증DAA-C01시험대비를 하시면 되겠습니다. 이렇게 어려운 시험은 우리Snowflake인증DAA-C01덤프로 여러분의 고민과 꿈을 한방에 해결해드립니다.

Snowflake인증 DAA-C01시험패스는 IT업계종사자들이 승진 혹은 연봉협상 혹은 이직 등 보든 면에서 날개를 가해준것과 같습니다.IT업계는 Snowflake인증 DAA-C01시험을 패스한 전문가를 필요로 하고 있습니다. Itexamdump의Snowflake인증 DAA-C01덤프로 시험을 패스하고 자격증을 취득하여 더욱더 큰 무대로 진출해보세요.

>> DAA-C01최신 인증시험 공부자료 <<

DAA-C01최신버전 시험덤프, DAA-C01최신버전 시험대비 공부문제

Snowflake DAA-C01인증시험패스에는 많은 방법이 있습니다. 먼저 많은 시간을 투자하고 신경을 써서 전문적으로 과련 지식을 터득한다거나; 아니면 적은 시간투자와 적은 돈을 들여 Itexamdump의 인증시험덤프를 구매하는 방법 등이 있습니다.

최신 SnowPro Advanced DAA-C01 무료샘플문제 (Q151-Q156):

질문 # 151
You are tasked with creating a dashboard to visualize sales performance across different product categories and regions. The data is stored in a Snowflake table named with columns: 'SALE DATE (DATE), 'PRODUCT CATEGORY (VARCHAR), 'REGION' (VARCHAR), 'SALES_AMOUNT (NUMBER). The business stakeholders want to see a trend of monthly sales for the past year, a breakdown of sales by region, and a comparison of sales between product categories. Which of the following approaches would be MOST effective and efficient in Snowflake for generating the data needed for these visualizations, considering the need for dashboard responsiveness and minimal query cost?

A. Create a single, complex SQL query that joins the 'SALES DATA' table with itself multiple times, using window functions and subqueries to calculate all the required aggregations and breakdowns within the query. The dashboard will directly query this view.
B. Create multiple materialized views, each specifically designed for one of the dashboard visualizations (monthly sales trend, sales by region, sales by product category). Refresh these materialized views regularly.
C. Create a data pipeline that transforms the raw 'SALES_DATX into summary tables using tasks and streams. These summary tables are optimized for the specific queries required by the dashboard visualizations.
D. Export the data to an external data warehouse for visualization purpose to avoid overhead of Snowflake visualization tool.
E. Use Snowflake's caching mechanism extensively to cache the results of individual queries within the dashboard, ensuring that subsequent requests for the same data are served from the cache. Rely on the dashboard's internal caching capabilities.

정답：B,C

설명：
Creating multiple materialized views (B) allows for pre-calculated aggregations tailored to each visualization, significantly improving dashboard responsiveness and reducing query costs. Using tasks and streams to transform the raw data into optimized summary tables (D) also pre-processes the data, providing similar benefits to materialized views, but allows for more complex transformations and incremental updates. A single complex query (A) can be slow and resource-intensive. Relying solely on caching (C) might not be sufficient for complex aggregations or large datasets. Exporting data to a completely new system adds overhead and is unnecessary given Snowflake's capabilities.

질문 # 152
You are analyzing website traffic data in Snowflake and notice a sudden drop in page views from a specific country (Country A) starting last month. You have access to the 'WEBSITE TRAFFIC' table with columns: 'date' , 'country', 'page_viewS, 'device_type'. Which of the following queries and techniques would be MOST effective in identifying the potential cause of this anomaly?

A. Join the 'WEBSITE_TRAFFIC' table with a table containing marketing campaign data (MARKETING CAMPAIGNS') on 'date' and 'country' to see if any marketing campaigns were paused or modified in Country A around the time of the drop. Consider using 'LEFT JOIN' to not lose traffic data.
B. Use a statistical anomaly detection function (e.g., moving average) on the 'page_views' for Country A and compare against other countries to identify if the drop is specific to Country A. Consider using 'LAG' function with 'OVER' clause to calculate the moving average.
C. Execute 'SELECT FROM WEBSITE_TRAFFIC WHERE country = 'Country A' AND date DATEADD(month, -1, CURRENT DATE());' and manually inspect the data for suspicious patterns.
D. Run a simple 'SELECT FROM WEBSITE_TRAFFIC WHERE country = 'Country A' AND date DATEADD(month, -3, GROUP BY date ORDER BY date;' to visualize the trend and confirm the drop.
E. Analyze 'page_viewS by 'device_type' for Country A before and after the drop to see if the drop is concentrated in a specific device type (e.g., mobile, desktop). Use 'CASE statement within the 'GROUP to categorize time periods.

정답：A,B,E

설명：
Options B, C, and D are the most effective. B uses statistical methods to identify the anomaly, C investigates potential external factors (marketing campaigns), and D explores internal segments (device types). Option A is a basic check but doesn't identify causes. Option E is not scalable and inefficient for large datasets. Using a combination of statistical analysis, external data integration, and segmentation provides a comprehensive diagnostic approach.

질문 # 153
Consider a scenario where you are building a dashboard to monitor the performance of a marketing campaign. The data includes daily ad spend, website conversions, and cost per acquisition (CPA). The stakeholders need to quickly assess whether the campaign is meeting its target CPA. What visualization type would be MOST appropriate to display the current CPA compared to the target CPA, providing a clear and concise view of performance?

A. A Pie chart showing CPA percentage against target CPA percentage.
B. A scatter plot showing the relationship between ad spend and CPA.
C. A line chart showing the trend of CPA over time.
D. A gauge chart displaying the current CPA and the target CPA, with color-coded zones indicating performance levels.
E. A bar chart comparing the average CPA to the target CPA.

정답：D

설명：
A gauge chart is specifically designed to display a single value (the current CPA) in relation to a target value (the target CPA). The color-coded zones provide an immediate indication of whether the campaign is performing well, needs improvement, or is failing. Line charts show trends, bar charts compare averages, and scatter plots show relationships. Pie chart showing CPA percentage against target CPA percentage do not accurately show CPA against target CPA, for better visualization gauge charts would be the preffered option

질문 # 154
A retail company wants to visualize sales performance across different product categories and regions. The business stakeholders need to identify both overall sales trends and granular insights into the performance of specific products in specific regions. They require a dashboard that allows for easy comparison of sales across categories and regions, highlighting best and worst performers. Which combination of chart types would be MOST effective for this dashboard, considering scalability and the need to avoid over-plotting?

A. A scatter plot comparing sales volume and profit margin for each product, a bar chart for sales by region, and a gauge chart indicating overall sales target achievement.
B. A heat grid showing sales by category and region, a time series chart for overall sales trends, and a treemap representing the contribution of each category to total sales.
C. A combination of bullet charts to show sales performance against targets for each region and category, a time series chart for overall sales trend, and a scatter plot showing discount vs quantity.
D. A geographical map visualizing sales by region with color-coded regions, a time series chart for overall sales trends, and a detail table for viewing sales by product categories.
E. A stacked bar chart for sales by category, a line chart for overall sales trend over time, and a pie chart for regional sales distribution.

정답：B

설명：
A heat grid effectively visualizes the relationship between two categorical variables (category and region) using color intensity, making it easy to identify high and low sales areas. A time series chart is appropriate for displaying trends over time. A treemap shows the proportional size of each category contributing to total sales. Stacked bar charts can become difficult to read with many categories and pie charts are not ideal for precise comparisons. Scatter plots are useful for correlation analysis (Sales vs Profit). A map would be good for high level visualization but not for specific numbers or precise details. Bullet charts are more suitable for target vs actual comparisons than a regional overview.

질문 # 155
A retail company wants to understand the relationship between promotional campaigns and sales uplift across different store locations and product categories. You have the following Snowflake tables: 'SALES': 'transaction id', 'store id', 'product_category', 'sale date', 'sale_amount' 'PROMOTIONS': 'promotion id', 'store id', 'product category', 'promotion start date', promotion_end_date', 'discount_percentage' Which analytical approach and corresponding SQL query would be MOST effective in determining if specific promotional campaigns consistently result in a statistically significant sales uplift, considering potential variations across different store locations and product categories? Assume you want to compare sales during the promotion period to a control period (before the promotion). (Select TWO)

A. Use a simple linear regression model in a Snowflake UDF (User-Defined Function) to predict sales based on the presence or absence of a promotion, without accounting for store or product category fixed effects.
B. Employ a difference-in-differences (DID) approach, comparing the change in sales from the control period to the promotion period for the 'treatment group' (stores/product categories with promotions) relative to the change for a 'control group' (stores/product categories without promotions). This requires careful identification of suitable control groups.
C. Run a series of AIB tests by randomly assigning different discount percentages to different stores and product categories during the promotion period and track the resulting sales uplift, using a Mann-Whitney U test for statistical significance.
D. Create a complex query that joins SALES and PROMOTIONS and calculates the percentage increase in sales during the promotion period compared to the average sales for the same store and product category in the 3 months prior, ignoring the potential for seasonality and other confounding factors.
E. Calculate the average sales amount for each store and product category during promotion periods and compare it to the overall average sales amount across all periods using a t-test or similar statistical test to determine significance. This would involve exporting data into a statistical tool.

정답：B,E

설명：
Options A and C are the most effective. Option A utilizes t-tests to assess the statistical significance of sales during promotion periods versus the overall average. Combining statistical analysis with Snowflake data extraction provides insightful results. Option C proposes the Difference-in-Differences (DID) approach which is very effective. It uses a control group to account for external factors that may have also influenced sales. Comparing treated (promotion stores) and controlled store to find the diff in diff provides statistically significant evidence. Options B and E are less rigorous. B doesn't account for important fixed effects and E doesn't consider seasonality and confounding factors. Option D suggests an AIB test which is not practical as sales can not be assigned randomly during a promotion.

질문 # 156
......

Itexamdump덤프를 IT국제인증자격증 시험대비자료중 가장 퍼펙트한 자료로 거듭날수 있도록 최선을 다하고 있습니다. Snowflake DAA-C01 덤프에는Snowflake DAA-C01시험문제의 모든 범위와 유형을 포함하고 있어 시험적중율이 높아 구매한 분이 모두 시험을 패스한 인기덤프입니다.만약 시험문제가 변경되어 시험에서 불합격 받으신다면 덤프비용 전액 환불해드리기에 안심하셔도 됩니다.

DAA-C01최신버전 시험덤프: https://www.itexamdump.com/DAA-C01.html

DAA-C01인증시험은 IT업계에 종사하시는 분들께 널리 알려진 유명한 자격증을 취득할수 있는 시험입니다, Itexamdump의 Snowflake DAA-C01덤프를 구매하기전 우선 pdf버전 덤프샘플을 다운받아 덤프문제를 공부해보시면Itexamdump덤프품질에 신뢰가 느껴질것입니다, IT업계에서 더욱 큰 발전을 원하신다면 DAA-C01자격증을 취득하는건 필수조건으로 되었습니다, DAA-C01시험을 빨리 패스해야 되는데 어디서부터 어떻게 시험준비를 시작해야 하는지 갈피를 잡을수 없는 분들은 저희 사이트를 주목해주세요, Snowflake DAA-C01인증은 아주 중요한 인증시험중의 하나입니다.

폴리의 총괄 부사장, 그런 이유로 사람을 죽이는 것이 괜찮다면 애시당초 너의 부모님이 돌아가신 것도 괜찮지 않아, DAA-C01인증시험은 IT업계에 종사하시는 분들께 널리 알려진 유명한 자격증을 취득할수 있는 시험입니다.

DAA-C01최신 인증시험 공부자료 덤프샘플문제 다운

Itexamdump의 Snowflake DAA-C01덤프를 구매하기전 우선 pdf버전 덤프샘플을 다운받아 덤프문제를 공부해보시면Itexamdump덤프품질에 신뢰가 느껴질것입니다, IT업계에서 더욱 큰 발전을 원하신다면 DAA-C01자격증을 취득하는건 필수조건으로 되었습니다.

DAA-C01시험을 빨리 패스해야 되는데 어디서부터 어떻게 시험준비를 시작해야 하는지 갈피를 잡을수 없는 분들은 저희 사이트를 주목해주세요, Snowflake DAA-C01인증은 아주 중요한 인증시험중의 하나입니다.