WILMINGTON, MA — Below are 5 things to do in Wilmington on Thursday, February 7, 2019:#1) Instant Pot Cooking Class At Wilmington LibraryThe Wilmington Memorial Library (175 Middlesex Avenue) is hosting “Feasting With Your Instant Pot” at 7pm. The instant pot craze is here, are you onboard? For many of us, the instant pot is patiently waiting to be used. Whether yours is tucked away in a cupboard or still in the box, it’s time to take it out your electric pressure cooker and put it to use. Join chef Liz Barbour for a cooking class that will help take the mystery out of this amazing, time saving kitchen tool. Liz will demonstrate two recipes that you can recreate at home. Following her demonstration Liz will offer tasty samples for everyone to enjoy. Registration is full, but there are still spots available on the waiting list HERE.#2) Drop-In Meditation At Wilmington LibraryThe Wilmington Memorial Library (175 Middlesex Avenue) is hosting a meditation class at 12:30pm. Join technology librarian Brad McKenna for his weekly drop-in meditation sessions. It will be a mixture of silent and guided meditations. The Insight Timer app will be used so you can continue your practice at home. No registration required.#3) Wilmington Recreation Commission MeetingThe Wilmington Recreation Commission meets at 5pm in Town Hall’s Room 9. Read the agenda HERE.#4) Wilmington Finance Committee MeetingThe Wilmington Finance Committee meets at 7pm in Town Hall’s Room 9. Budgets for Planning & Conservation, Building Inspector, and Board of Appeals will be discussed. Rea the agenda HERE.#5) Tour Of Wilmington Town MuseumThe Town Museum (430 Salem Street) is open from 10am to 2pm. Come explore Wilmington’s history. Free admission.Like Wilmington Apple on Facebook. Follow Wilmington Apple on Twitter. Follow Wilmington Apple on Instagram. Subscribe to Wilmington Apple’s daily email newsletter HERE. Got a comment, question, photo, press release, or news tip? Email email@example.com.Share this:TwitterFacebookLike this:Like Loading… Related5 Things To Do In Wilmington On Thursday, September 5, 2019In “5 Things To Do Today”5 Things To Do In Wilmington On Thursday, August 8, 2019In “5 Things To Do Today”5 Things To Do In Wilmington On Tuesday, August 13, 2019In “5 Things To Do Today”
Floral fashion is never out of trend, but it helps to know how to get it right and not go overboard.Fashion experts have shared tips that can help you style your floral outfits for different occasions to add spark to your look:-Florals for workwear: Floral print mostly in dresses is on the top of this season’s trend alert. One can easily incorporate some florals in the workwear wardrobe. Go for minimal silhouettes and elegant prints. You can style a nice muted floral sheath dress with a leather belt, a longline blazer and a nice pair of black heels. A floral shirt with a solid skirt would also be a great hit at your workplace. Also Read – Add new books to your shelf-Florals for evening looks: People often connect florals with a breezy morning brunch or a sunny afternoon stroll but it could be a nice evening wear option too. All you have to do is to go for a floral print over a rich fabric like silk, satin or organza. You can also go for a quite elaborate silhouette and can finish the look with a statement pair of earrings and nice contrasting pumps.-Florals for fall: Fall season rings the bells for winters but it doesn’t mean that you can’t wear floral dresses in fall. For fall, one should opt for some earthy florals over chirpy ones. You can incorporate colours like slightly rustic shade of orange; go for floral printed mustards or a shade of lavender. You can style your floral skirts with tinted full sleeve blouses and you can wear your floral dresses as a layer over a basic t-shirt or shirt and can complete the look with a nice pair of boots and some chunky accessorizing would do magic to the whole ensemble. Also Read – Over 2 hours screen time daily will make your kids impulsive-Florals for casual getaways: A floral print short dress can be a very sophisticated and playful choice. A go-to option for casual getaways the colours of the dress can be anything from vibrant to bright or neutral. A solid black dress or anything in a darker hue is usually better suited for the cold weather. Boots and scarves can be matched to give a complete winter vibe to your outfit. Long floral shrugs are also great add-ons for a chic and breezy look in the fall season. -Florals for a picnic: The year is not complete without at least one meal eaten alfresco in the park or by the beach. Also, because the ambience and scenery around are just begging to be Instagrammed, you’re going to want to wear the right picnic outfit. Find something that keeps you comfortable like a nice floral blouse paired with comfortable linen pants. A floral dress paired with a solid scarf also makes for a great outfit choice! You can also choose long floral shrugs instead and as they add a rich look to any dress.
December 12, 2013 Opinions expressed by Entrepreneur contributors are their own. 5 min read There’s hard work. And then there’s luck. But there’s also that something else that makes all the difference. And it’s that edge that differentiates the most successful apps from the rest of them.Of course, there’s one thing that you cannot ignore, and that is building a product that customers want. Considering that you’ve built a fantastic product, not just in your own eyes but validated through customer feedback, read on for what made these apps a roaring success.Instagram: Invite influential people to your beta launch.Founder Kevin Systrom let some influential technology bloggers and contacts — like Jack Dorsey of Twitter — try a test version of the app before its official release. Soon, Dorsey was using it to send photos to his Twitter followers. Word eventually spread. Of course, two articles in TechCrunch (one before launch and one on the day of the launch) helped along with word of mouth.From 25,000 users in the first 24 hours, Instagram grew to 300,000 by its third week, and then into the tens of millions.What also made a difference in the initial traction was that Instagram launched right after the release of the iPhone 4, which included a much-improved screen and camera. The company also went against the grain by making it easy to push photos from the app into social networks like Facebook and Twitter, rather than locking the photos in the app. Then, a trick to upload photos super-fast made all the difference to users who wanted the experience in that very moment. Instagram managed to ‘hide the slowness’ by beginning the upload process as soon as photos are taken and by using a relatively small photo size.Snapchat: Get your target customers buzzing.The founders first spread the word about Snapchat to college friends at Stanford University, but the app’s popularity didn’t really start to take-off until it made its way into the high school ranks to become a popular means of communication for teenagers.One user best highlights its secret sauce to viral growth: its group messaging functionality. When a user sends a snap to multiple friends, the recipients receive a snap indistinguishable from an individualized message. In effect, mass snaps feel personalized. This is the holy grail of messaging platforms: evoking strong emotion with minimal friction.Of course, since snaps disappear seconds after they are opened, users feel comfortable sending spontaneous and personal messages that they would not want ingrained into digital histories.Evernote: Get press attention.In an interview to doeswhat, Phil Libin mentioned what helped Evernote grow exponentially from Day One to more than a million users was the initial press coverage and a closed beta.TechCrunch wrote about Evernote’s closed beta which ignited the spark for its growth. Within days of the coverage, Evernote received a couple thousand signups for its beta. And the first set of users who loved the product helped spread the word around.What Evernote also did as a strategy in the first couple of years from launch was to obsess about being in all the app store launches on Day One. With every new device or platform launch, the company had the app ready to be submitted. This helped Evernote become one of the showcase apps for all the devices as they launched.Clear: Be unique. Be simple.It all started with building an app that was a major leap forward in app design. With no buttons at all, this app’s uniqueness was the simplicity of use in a highly cluttered and complex set of to-do list apps. The kicker for the app was in its design or usability with a no-nonsense interface, dominated by natural interaction instincts, stripping it bare of all complex features (often tagged with to-do apps), but one — maintaining a list, quickly and in a fun way.The founders of the Clear app were “clear” in their marketing strategy. They went all out to get tech blog coverage based on demos, previews and teaser videos even before it went to market and sold 350,000 copies within nine days of its launch. They invited select members of the media to beta-test the app and to see if the app caught their fancy.A video demo uploaded to Vimeo during the MacWorld conference in January 2012 — where Clear was being shown off for the first time — has been watched more than 814,000 times so far, also built buzz for the app’s launch in February 2012.Camera+: Be aggressive on social.The founders of Camera+ chose to go big on the launch of their app and went with the most popular social services that were most relevant to their app spread via word of mouth. They chose Flickr, Facebook, Twitter and email for Camera+ and making the sharing feature better than any other similar feature out on the app store.The launch promotion included a contest for $10,000+ worth of camera equipment and got the word out to their existing mailing list of about 70,000 subscribers.One of the other insights they had was not to solely depend on domestic sales. The founders realized that apart from the US, many other countries do not have games dominate the top charts. They drew large crowds from international markets, many places becoming Apple’s App of the Week.Their co-founder posted a video on their blog that demonstrated the main feature that was going into version 1.2. No one had this feature available and this post created a lot of buzz for them and helped sustain the enthusiasm through the months.
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
The Windows 10 October update was available for download around the time of the Surface event last week. While the update brought features like Your Phone App and Windows Timeline, users also experienced massive file deleting from their systems. Microsoft had excluded the update from some devices due to compatibility issues with newer processors. The issue was reported by users in the early stages before mass rollout. Users could manually download and install the Windows October 2018 Update from October 2. Rollout was to be pushed October 9 for Patch Tuesday. Microsoft recommends contacting their customer support if the update has deleted your files. The support site advices: “If you have manually downloaded the Windows 10 October 2018 Update installation media, please don’t install it and wait until new media is available.” As of now, it is not known how many users faced this issue. Windows updates are not known to be smooth, causing some issues and errors. But it is unusual that an issue of this magnitude was not detected in Microsoft’s testing of the Windows update. Earlier this year, Microsoft had delayed the Windows 10 April 2018 because of Blue Screen of Death issues. But the issues in that update were rectified before the update reached regular users. Fortunately, this update wasn’t mass rolled out and the issue was detected in an early stage. This serves as a reminder to users to create a backup of important files before an OS update. When Microsoft continues mass rollout of this update, the issue will be fixed, but it is safe to backup your data in any case. The official support page states: “We have paused the rollout of the Windows 10 October 2018 Update (version 1809) for all users as we investigate isolated reports of users missing some files after updating.” There are comments on the support page, where users are stating the problem. For more details visit the Microsoft support website. Read next Microsoft Your Phone: Mirror your Android phone apps on Windows What’s new in the Windows 10 SDK Preview Build 17704 Microsoft Cloud Services get GDPR Enhancements