Twitter Emily Gao considers herself an engineer as much as a jewellery designer.The 25-year-old Torontonian behind the accessories line JY Gao harnesses everyday kinetic energy to create jewellery with independent moving parts that swing, dangle, and oscillates when activated by the movement of the wearer. “It’s partly engineering because you envision something to look great, but when you actually test it out on the human body, it might not have the same effect,” Gao says of the trial-and-error process. She often prototypes her designs using inexpensive materials such as hinges from hardwares stores before rendering the finished product using sterling silver. (If the term ‘kinetic jewellery’ sounds unfamiliar that’s because “its something I sort of invented,” she says.)Currently, JY Gao is an under-the-radar accessories label founded in 2016 (a pair of the label’s earrings appeared in a shoot in the October 2018 issue of FASHION), but it may not stay that way for long, since Gao received a massive cash infusion after winning second place in China’s largest design competition, which awards cash prizes in excess of $1 million. (In comparison, the prestigious LVMH Prize gives out one 300,000-euro and one 150,000-euro prize each year.) Login/Register With: Facebook Advertisement Advertisement LEAVE A REPLY Cancel replyLog in to leave a comment Advertisement
“We’d just seen that our audience had been changing in how they consume media,” Izzo says. “A big part of the change for us was the significant adoption of mobile and the engagement on social media.”Izzo says ALM made a big effort to transform into a digital-first company as a result. Another factor that contributed to the program’s creation was the significant increase in traffic on ALM websites from mobile devices, an increase of around 80 percent July over July from last year, according to Izzo.“Digital membership establishes a simple way for us to serve today’s subscribers and future subscribers with the online news content they want, when and where they want it,” says Jeffrey S. Litvack, chief digital officer at ALM in a statement.The free membership package includes digital access to five news articles every month from three controlled circulation publications, online access to news alerts, newsletters and previously archived news stories, and discounts on ALM products and services.“Subscribers will now have an easier way to click through to the content they want to read and non-subscribers will have a viable option for continuing to read by viewing five free stories a month,” Litvack contends.UPDATE: This movement of content from behind the paywall to the forefront with free access is a key advantage for subscribers, says Izzo.“The benefit to paid members is the ability to share the content to colleagues and potential clients,” Izzo says. “This ability to pass on a story to a colleague digitally makes that sharing process, either from social media or from your inbox newsletter, easier.”Digital membership holders have free and unlimited online access to three controlled circulation publications: Corporate Counsel, Law Technology News and The Asian Lawyer. ALM maintains that their four paid premium publications—Supreme Court Brief, Litigation Daily, New Jersey Law Journal Decision Alert and Delaware Business Court Insider—will continue to be accessible only to each publication’s subscribers. Paid subscribers will also maintain exclusive access to premium reports and briefings, including the Am Law 100 report.UPDATE: The decision to only allow five free news articles per monthly cycle was a strategic move on ALM’s part.“We want non-paid subscribers to test, trial, read and consume at least five articles a month across the network,” Izzo contends. “We felt that five was reflective of the engagement level of our readers on a daily, weekly and monthly basis.”More on this topic ALM Forms New Marketing Services Team InsideCounsel Folds Print Edition People on the Move | 5.17.12 ALM Newsletter Open Rates Jump 60 Percent After Mobile Optimization ALM Expands Regional Publishing Services Jeffrey LitvackJust In Meredith Corp. Makes Digital-Side Promotions | People on the Move Bonnier Corp. Terminates Editor-in-Chief for Ethics Breach The Atlantic Names New Global Marketing Head | People on the Move BabyCenter Sold to Ziff Davis Parent J2 Media | News & Notes This Just In: Magazines Are Not TV Networks Four More Execs Depart SourceMedia in Latest RestructuringPowered by ALM is set to launch a free digital membership program for legal professionals later this month.The legal and commercial real estate news publisher is looking to expand its consumer base by offering a bundled news service package that includes five free articles a month, newsletters, news alerts and access to ALM’s database where some previously archived subscriber-only stories will now be made available. The digital reader program, launching August 23, 2013, is cost-free.UPDATE: The catalyst for the creation of the digital membership program, according to ALM SVP and chief marketing officer Lenny Izzo, is mainly consumer convenience.
National Journal has announced several new additions to it leadership team. These hires come as the brand looks to beef up its political coverage. Stephanie Craig joins the brand as executive director of marketing and communications. A veteran of Capitol Hill, Parliament Hill in Ottawa, the campaign trail and the Washington trade association world, Craig brings a unique perspective and experience in communications and marketing in Washington. Angela Salazar has been named senior editor at InStyle. She had been deputy style editor at The San Francisco Chronicle. Additionally, Johnson Publishing Company has named Chan C. Smith its multimedia producer. She had been content creator at Chan C. Smith Media. Jenny Jin has been named editor at PureWow. She had been associate beauty editor at Real Simple. IBT Media announced that Arbell Noach has joined the marketing team as VP, director of social media. Noach joins IBT Media from Doremus where she was the engagement lead focusing on content, social media and influencer and experiential marketing. Joining Craig on the marketing and communications team is Shannan Bowen as director of audience strategy. Bowen returned to Atlantic Media earlier this fall from The Hill, where she served as Director of Audience Engagement, where she guided the development of a new mobile site and managed an audience development strategy that set records for the publication’s mobile traffic and Facebook engagement. Danielle Whelton joins National Journal as the senior director of membership services, overseeing the team serving the brand’s more than 1000 member organizations with custom research and strategy services. Prior to leaving journalism, Whelton spent five years as senior executive producer of CNN’s White House Unit. LaToya Cross has been named social media manager, Jet, and digital editor at Johnson Publishing Company. She had been associate editor at N’Digo Magapaper. Here are the rest of this week’s people on the move:
India’s Biggest Food Truck Festival , the Delhi Food Truck Festival (DFTF) 2017, a two day affair finally came to an end and captured many eyeballs for not only being conducted at a massive level but also for being the first food truck event to offer plethora of fun and engaging activities. The fest had already been trending up ever since its inception and has become a buzzword in the culinary circles for showcasing the best of the Food Trucks!History says the first food truck festival was conducted in Los Angeles and post then, food truck festivals have been happening in all parts of the world such as Chicago, New York, Berlin etc. With the trend emerging in India, the Capital was expected to host a Big Show after being recently conducted in Bangalore and Bombay and DFTF 2017 left no stone unturned for this to happen! Also Read – Add new books to your shelf’We had incorporated many authentic activities to create a wholesome experience for all kind of audiences,” said Shivangi Gupta, one of the organisers. Talking about the vision she says, ‘Being the debut, we were not focusing on the commercial success but wanted all the visitors to have a good time and have a one-of-a-kind experience and feel the difference”.Delhi Food Truck Festival powered by India Gate Basmati Rice, was an initiative by VMS Events and Radio City 91.1 and saw 18k people attending the fest during both the days.Be it Rain Dance to soothe everyone amidst Delhi’s 42’c heat, or live Performances by Jassie Gill and Babbal Rai on Baisakhi to Witlinger adding a craft beer flavour to the food for beverage connoisseurs, all fascinated the food aficionados and kept hem expecting for more fun at Delhi’s biggest Food Truck Festival.
Microsoft Power BI Desktop contains a rich set of data source connectors and transformation capabilities that support the integration and enhancement of source data. These features are all driven by a powerful functional language and query engine, M, which leverages source system resources when possible and can greatly extend the scope and robustness of the data retrieval process beyond the possibilities of the standard query editor interface alone. As with almost all BI projects, the design and development of the data access and retrieval process has great implications for the analytical value, scalability, and sustainability of the overall Power BI solution. Our article is an excerpt from the book Microsoft Power BI Cookbook, written by Brett Powell. This book shows how to leverage Microsoft Power BI and the development tools to create better data driven analytics and visualizations. In this article, we dive into Power BI Desktop’s Get Data experience and go through the process of establishing and managing data source connections and queries. Examples are provided of using the Query Editor interface and the M language directly to construct and refine queries to meet common data transformation and cleansing needs. In practice and as per the examples, a combination of both tools is recommended to aid the query development process. Viewing and analyzing M functions Every time you click on a button to connect to any of Power BI Desktop’s supported data sources or apply any transformation to a data source object, such as changing a column’s data type, one or multiple M expressions are created reflecting your choices. These M expressions are automatically written to dedicated M documents and, if saved, are stored within the Power BI Desktop file as Queries. M is a functional programming language like F#, and it’s important that Power BI developers become familiar with analyzing and later writing and enhancing the M code that supports their queries. Getting ready Build a query through the user interface that connects to the AdventureWorksDW2016CTP3 SQL Server database on the ATLAS server and retrieves the DimGeography table, filtered by United States for English. Click on Get Data from the Home tab of the ribbon, select SQL Server from the list of database sources, and provide the server and database names. For the Data Connectivity mode, select Import. A navigation window will appear, with the different objects and schemas of the database. Select the DimGeography table from the Navigation window and click on Edit. In the Query Editor window, select the EnglishCountryRegionName column and then filter on United States from its dropdown. Figure 2: Filtering for United States only in the Query Editor At this point, a preview of the filtered table is exposed in the Query Editor and the Query Settings pane displays the previous steps. Figure 3: The Query Settings pane in the Query Editor How to do it Formula Bar With the Formula Bar visible in the Query Editor, click on the Source step under Applied Steps in the Query Settings pane. You should see the following formula expression: Figure 4: The SQL.Database() function created for the Source step Click on the Navigation step to expose the following expression: Figure 5: The metadata record created for the Navigation step The navigation expression (2) references the source expression (1) The Formula Bar in the Query Editor displays individual query steps, which are technically individual M expressions It’s convenient and very often essential to view and edit all the expressions in a centralized window, and for this, there’s the Advanced Editor M is a functional language, and it can be useful to think of query evaluation in M as similar to Excel spreadsheet formulas in which multiple formulas can reference each other. The M engine can determine which expressions are required by the final expression to return and evaluate only those expressions. Configuring Power BI Development Tools, the display setting for both the Query Settings pane and the Formula bar should be enabled as GLOBAL | Query Editor options. Figure 6: Global layout options for the Query Editor Alternatively, on a per file basis, you can control these settings and others from the View tab of the Query Editor toolbar. Figure 7: Property settings of the View tab in the Query Editor Advanced Editor window Given its importance to the query development process, the Advanced Editor dialog is exposed on both the Home and View tabs of the Query Editor. It’s recommended to use the Query Editor when getting started with a new query and when learning the M language. After several steps have been applied, use the Advanced Editor to review and optionally enhance or customize the M query. As a rich, functional programming language, there are many M functions and optional parameters not exposed via the Query Editor; going beyond the limits of the Query Editor enables more robust data retrieval and integration processes. Figure 8: The Home tab of the Query Editor Click on Advanced Editor from either the View or Home tabs (Figure 8 and Figure 9, respectively). All M function expressions and any comments are exposed Figure 9: The Advanced Editor view of the DimGeography query When developing retrieval processes for Power BI models, consider these common ETL questions: How are our queries impacting the source systems? Can we make our retrieval queries more resilient to changes in source data such that they avoid failure? Is our retrieval process efficient and simple to follow and support or are there unnecessary steps and queries? Are our retrieval queries delivering sufficient performance to the BI application? Is our process flexible such that we can quickly apply changes to data sources and logic? M queries are not intended as a substitute for the workloads typically handled by enterprise ETL tools such as SSIS or Informatica. However, just as BI professionals would carefully review the logic and test the performance of SQL stored procedures and ETL packages supporting their various cubes and reports environment, they should also review the M queries created to support Power BI models and reports. How it works Two of the top performance and scalability features of M’s engine are Query Folding and Lazy Evaluation. If possible, the M queries developed in Power BI Desktop are converted (folded) into SQL statements and passed to source systems for processing. M can also reduce the required resources for a given query by ignoring any unnecessary or redundant steps (variables). M is a case-sensitive language. This includes referencing variables in M expressions (RenameColumns versus Renamecolumns) as well as the values in M queries. For example, the values “Apple” and “apple” are considered unique values in an M query; the Table.Distinct() function will not remove rows for one of the values. Variable names in M expressions cannot have spaces without a hash sign and double quotes. Per Figure 10, when the Query Editor graphical interface is used to create M queries this syntax is applied automatically, along with a name describing the M transformation applied. Applying short, descriptive variable names (with no spaces) improves the readability of M queries. Query folding The query from this recipe was “folded” into the following SQL statement and sent to the ATLAS server for processing. Figure 10: The SQL statement generated from the DimGeography M query Right-click on the Filtered Rows step and select View Native Query to access the Native Query window from Figure 11: Figure 11: View Native Query in Query Settings Finding and revising queries that are not being folded to source systems is a top technique for enhancing large Power BI datasets. See the Pushing Query Processing Back to Source Systems recipe of Chapter 11, Enhancing and Optimizing Existing Power BI Solutions for an example of this process. M query structure The great majority of queries created for Power BI will follow the let…in structure as per this recipe, as they contain multiple steps with dependencies among them. Individual expressions are separated by commas. The expression referred to following the in keyword is the expression returned by the query. The individual step expressions are technically “variables”, and if the identifiers for these variables (the names of the query steps) contain spaces then the step is placed in quotes, and prefixed with a # sign as per the Filtered Rows step in Figure 10. Lazy evaluation The M engine also has powerful “lazy evaluation” logic for ignoring any redundant or unnecessary variables, as well as short-circuiting evaluation (computation) once a result is determinate, such as when one side (operand) of an OR logical operator is computed as True. The order of evaluation of the expressions is determined at runtime; it doesn’t have to be sequential from top to bottom. In the following example, a step for retrieving Canada was added and the step for the United States was ignored. Since the CanadaOnly variable satisfies the overall let expression of the query, only the Canada query is issued to the server as if the United States row were commented out or didn’t exist. Figure 12: Revised query that ignores Filtered Rows step to evaluate Canada only View Native Query (Figure 12) is not available given this revision, but a SQL Profiler trace against the source database server (and a refresh of the M query) confirms that CanadaOnly was the only SQL query passed to the source database. Figure 13: Capturing the SQL statement passed to the server via SQL Server Profiler trace There’s more Partial query folding A query can be “partially folded”, in which a SQL statement is created resolving only part of an overall query The results of this SQL statement would be returned to Power BI Desktop (or the on-premises data gateway) and the remaining logic would be computed using M’s in-memory engine with local resources M queries can be designed to maximize the use of the source system resources, by using standard expressions supported by query folding early in the query process Minimizing the use of local or on-premises data gateway resources is a top consideration Limitations of query folding No folding will take place once a native SQL query has been passed to the source system. For example, passing a SQL query directly through the Get Data dialog. The following query, specified in the Get Data dialog, is included in the Source Step: Figure 14: Providing a user defined native SQL query Any transformations applied after this native query will use local system resources. Therefore, the general implication for query development with native or user-defined SQL queries is that if they’re used, try to include all required transformations (that is, joins and derived columns), or use them to utilize an important feature of the source database not being utilized by the folded query, such as an index. Not all data sources support query folding, such as text and Excel files. Not all transformations available in the Query Editor or via M functions directly are supported by some data sources. The privacy levels defined for the data sources will also impact whether folding is used or not. SQL statements are not parsed before they’re sent to the source system. The Table.Buffer() function can be used to avoid query folding. The table output of this function is loaded into local memory and transformations against it will remain local. We have discussed effective techniques for accessing and retrieving data using Microsoft Power BI. Do check out this book Microsoft Power BI Cookbook for more information on using Microsoft power BI for data analysis and visualization. Read Next: Expert Interview: Unlocking the secrets of Microsoft Power BI Tutorial: Building a Microsoft Power BI Data Model Expert Insights:Ride the third wave of BI with Microsoft Power BI