Aesthetic Workshop 2017 Consists Of Microsoft Business Intelligence Tools.

Aesthetic Workshop 2017 Consists Of Microsoft Business Intelligence Tools. – In my last blog, I introduced DAX and we created a column and measure. In this blog post, we’ll go over how to use time information in Power BI using DAX. You can convert data using periods such as years, quarters, months, and days and perform calculations on those periods. The most common time periods we encounter in business models are Year-to-Date, Quarter-to-Date, Month-to-Date, Last Year Full Year, and Rolling 12 Months. There are many other time-sensitive functions in DAX. You can find the full list of time-sensitive activities here.

To use time functions in Power BI, you need to have a table that contains one column that contains a date data type. This column requires only one row per day for a range of dates without spaces. In our example, we have a “Calendar” section that has a column called “Day” which is a date column.

Aesthetic Workshop 2017 Consists Of Microsoft Business Intelligence Tools.

Now that we have our requirements for using Time Intelligence functions in Power BI let’s start doing some. We will make these calculations in our Purchase table.

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The TTALYTD function returns the year-to-date corresponding to the last date in our calendar measure or year_end_date that we specified. The SUM function will add the wrong number to the SalesAmount column.

The TOTALQTD function returns the quarter-to-day by evaluating all the days in the current quarter to date. Filtering is optional to apply to the current context.

The syntax and function is the same as TOTALQTD except this is for the month to date.

This calculation is slightly different than the three numbers. In this case, we need to use a function called SAMEPERIODLASTYEAR to change the date one year to the time from the date specified in our date column. We are using the CALCULATE function instead of SUM because CALCULATE can change the filter context and use SAMEPERIODLASTYEAR as the filter.

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Rolling 12 Months is very different than any other timeline we’ve done so far. There are other ways to achieve this number, however, we will use the one in this example. We use the purchase date from our actual purchase schedule rather than the calendar date.

Let us read the word from within. We take the highest sales date from the actual sales table to give us a solution to the data. After that, the date function DATESINPERIOD (DATESINPERIOD(, , , )) contains a column of dates starting with start_date, in our case the last date We have a purchase history. in our actual sales table, and continue for the specified number_of_intervals. Since we are looking at a 12-month period, our number of periods is 12. Also, note that in the DATESINPERIOD function we specified when to convert the dates as months. We can use year, quarter, or day.

The time tracking functions in Power BI allow you to perform calculations on multiple time points and related time points. We know how to make today’s numbers for the year, month, and quarter. Also, we have extended our calculations to last year and 12 months. These functions give us the flexibility to show time. These real-time insights can be used at any Power BI license level, but a Power BI Pro license is required to share data and reports with Pro license holders. Click here to read more about Power BI Free vs Pro. Additionally, you can increase your reporting detail and improve your data visibility by setting up a Power BI Hierarchy.

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Model business intelligence systems using decision-making capabilities and concepts with the lens of individual, technology, organization, and environment.

Department of Conservation Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam

Received: 16 April 2020 / Revised: 28 April 2020 / Accepted: 29 April 2020 / Published: 4 May 2020

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Industry 4.0 makes society more competitive and puts pressure on companies to integrate advanced technologies. The business intelligence system (BIS) is one of the most important technologies that have attracted the attention of policy makers and business experts due to its ability to provide information and intelligence for decision-making processes. . The literature shows that organizations and businesses can integrate BIS in a big way, but more than 70% BIS programs do not deliver the expected results. Therefore, it is necessary to explore the important determinants of BIS adoption and acceptance in organizations. Although previous literature lacks a comprehensive analysis of human, technological, organizational, and environmental determinants. Therefore, the present study attempts to reduce this gap by a systematic literature review (SLR) of 84 studies published during the period of 2011–2020. A total of 93 decision makers were identified based on information analysis using Yoshikoder’s text mining techniques and statistical skills. The identified determinants are ranked according to frequency of use. A conceptual framework with determinants and themes was developed. The research results will expand the new BIS literature and improve the understanding of the decision-making processes of professionals to take advantage of the benefits of BIS adoption.

Businesses are becoming increasingly complex in the era of Industry 4.0. Therefore, companies need new products and technologies to quickly respond to dynamic markets [1, 2]. The emergence of Business Intelligence Systems (BIS) was driven by the rapid development of technology and the spread of the Internet in the mid-90s [3, 4]. BIS is seen as a comprehensive set of tools, techniques, and methods that enable companies to integrate and analyze large data sets in order to identify their weaknesses, strengths, and with opportunities [5, 6, 7]. BIS is an information system (IS) that facilitates decision-making by (i) managing, integrating and integrating unstructured and structured data, (ii) dealing with big data such as general data, (iii) provide ad-hoc questions, reports. , forecasting, and editing, (iv) support end users with advanced editing skills to find new information [3, 8]. BIS can strengthen the internationalization process of companies by sorting, summarizing, analyzing and combining data from many sources [9], such as competitors, markets hospitality, and local government [10]. In today’s business, due to hyper-competition and technological progress with big data [11, 12]. BI technology is positioned among the best technical elements of decision-making powers including business owners, chief executive officers (CEO) and chief information officers [3, 13, 14].

In order to compete in traditional or online markets, BI companies have gained a lot of attention for providing better products and services with better processes and management practices [15]. It is shown by the increase of the global BIS market that increased by about 7.3% in 2017, with revenues up to $ 18.3 and it is expected to reach $ 22.8 billion by the end of 2020 [3, 16]. It has been found by previous researches, that companies cannot take advantage of the real benefits from adopting BIS [3, 14, 17, 18]. Despite its importance, market expansion and investment growth, more than 70% BI projects do not deliver the expected results [3, 17, 19]. Companies are struggling to find the best decision makers to implement their BIS and big data integration successfully by providing the highest benefits from the

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