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WhatsApp has turned into another app you turn to to find a specific file. Sure, you may already have a file manager installed, but you usually look for the file there if you’re already on the app. For a long time, the WhatsApp search tool needed a lot of improvement, but, not too long ago, it got a much-need update.
Since the feature is new, you could accidentally do something that you’ll definitely regret later. The new WhatsApp search tool is easy to use, but it doesn’t hurt to read up on some tips before using it, right?How to Get the Most out of WhatsApp’s New Search Feature
If you have no idea what conversation the file you’re looking for is in, you can do a general search. To do that, open WhatsApp and tap on the magnifying glass option at the top. The app will show you option such as:
For example, let’s say you’re looking for an audio. Tap on the audio option, and WhatsApp will show you all the audios you’ve received, starting with the most recent. Searching for the audio this way can’t take a lot of time. To speed things up a little, type the name of the person that sent you the audio. After typing a few letters, the app will group together all the audios from that person.
But, at the top, WhatsApp will give you the option to chose from different names. Since you’re looking for an audio, you’ll see options such as From John or From Sara. Tap on the name you think the audio you need is in to see them all.
Things get slightly different when you’re looking for files such as photos and GIFs since it shows you more information. For example, if you’re looking for a picture, you can see who the picture was from by changing the layout by tapping on the top’s layout icon.
As you can see from the image above, you’ll see the name along with the GIF the other person sent, but you’ll also see the ones you sent as well.How to Search for Files on for a Specific WhatsApp Contact
To find a file from a particular contact, tap on the search option at the top. Type the name of the contact, and at the bottom, WhatsApp will show the latest messages from the contact, and in the middle or top, you’ll see the type of files you can search for.
For example, if you want to look for a specific image from that contact, tap on the Photos option. The first image you’ll see will be the latest one you received or sent that contact. Since you already know who the file is from, it’s best to see the images as big as possible since it’s easier to read when those images were sent.Conclusion
There’s always room for improvement, but the update that the WhatsApp search tool received is great. These changes are a must if WhatsApp wants to keep its users, not only make them stay but keep them happy. What are your thoughts on the feature?
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But to understand how it works, you need to get much better at understanding virtual tables. Virtual tables are a key concept when utilizing DAX measures within Power BI.
What the INTERSECT function specifically does is that it allows you to – within a measure – compare one virtual table to another one. You will then finally be able to return a table of results that appear in both versions of these two virtual tables.
In the example that I run through, I’ll showcase a really unique insight that you can discover using the INTERSECT function. This particular insight can be re-used in many different ways. This is most useful when you’re working with customer data and your aim is to understand your customers better.
The best way to learn this function is through a practical scene. So, I’m going to work through a scenario and work this out based on our customers for the current month. These customers should also have a purchase history for the past two months. And we’re going to figure out which of our current customers had previous order transactions from 2 months ago.
Take a look at this Power BI report that I’ve created to demonstrate the INTERSECT function. First, I’ve set up some filters on the left-hand side where we can select any month.
Then, I have the columns for all the customers. The Total Sales and Sales LM columns show the customers who have purchased histories for the current month as well as for the last month. The formula for Total Sales is very simple. It’s just the sum of all the sales from a certain customer.
The Sales LM formula is a simple total sales formula branching out into a time intelligence calculation using DATEADD to jump back to the previous month.
It’s important to understand the initial context of the formula since we’re enabling a calculation of last month using the mentioned formulas. Thus, we need to get the initial context right so that we can apply the DAX formulas.
How do we dynamically work out the customers who purchased two months in a row? That’s what you can see in the Customers 2M in A Row column.
Now, I also want to know the total sales from these customers so I’ve added the Sales from Customers 2M in A Row column.
Let’s take a look at how useful INTERSECT is when it comes to finding out the repeat customers. Here’s the formula for Customers 2M In A Row.
In this formula, I placed two virtual tables, which are out variables (VAR) inside the INTERSECT function. Basically, it evaluates the list of items or rows that are present in the first table, but not in the second one.
The initial table here is CustomerTM which stands for those customers who have purchased this month. Then, the formula proceeds to check whether or not these customers are also listed in the CustomerLM table.
If a customer exists in both of the virtual tables, they will be retained. Thus, this formula allows us to end up with all the customers who purchased this month and the month before.
Next, I used the COUNTROWS function to count those remaining customers.
Now, let’s talk about creating virtual tables for those customers who have purchased for 2 months in a row.
If you have noticed, I put them inside the VAR (variables) function. I highly recommend these functions as they are a fantastic addition to writing more complex formulas.
In this particular set for VAR CustomerTM, I’m creating a virtual table of customer IDs. Then, for VAR CustomerLM, I’m creating a virtual table again for our customers last month. But this time, I’ve added the CALCULATETABLE function, so that it can jump back to the customer set of the previous month instead of the current context.
Here’s what’s interesting about this calculation that we have now.
The formula only checks every single row of the customers because the customers are filtered. If there is no sales for the previous month for a specific row (customer), there is nothing to evaluate. Thus, the Customers 2M In A Row column is blank. But if a customer has a previous record, it then counts as 1.
For instance, if we look at the data for Adam Thompson, it returns 1 under the Customers 2M In A Row column. This means that this customer has a record for both last month and the two months before that.
You might not realize the importance of using INTERSECT right away, but there’s a really good reason why you need to use this formula. It’s mainly because you can reuse this calculation across a wide variety of contexts. Take a look at this example below.
To come up with the sample data above, I just used the same formula. But this time, I’m starting in a different initial context. Instead of evaluating one single row, it evaluates many contexts like the State Code. And then, it creates a list of customers who purchased in June 2023 as well as in May 2023. Then, I’ll compare it to those customers who purchased once in a particular state in the current month.
You can see in the Customers 2M In A Row column the exact count of customers matching up to that criteria.
Below that table is another visualization that showcases the same data for Customers 2M In A Row by State Code.
You can actually change the context in your model again depending on your requirements. If your filter is working correctly, you can reapply this formula to add to other situations.
This is why I said that INTERSECT is very powerful. Instead of just writing IF statements, you can utilize these INTERSECT functions to your formula.
Moreover, we work on the total number of sales from our repeat customers.
The results in the Sales from Customers 2M In A Row column is the sum of the customer’s purchase for the current month and the previous one. Take note that we can only get this result if the customer has purchased for two months in a row.
This is the formula for the total sales of the repeat customers.
You can see here that the pattern is almost exactly the same. The only difference here is that instead of COUNTROWS, I used the CALCULATE function to change the context of the calculation.
This is because what we need here is the total amount of sales from the customers. But as you can see, I’m still using the INTERSECT function. It’s very helpful when it comes to Pareto Analysis. But you can also apply this function in a number of different ways.
You can still take things further than before. You can actually calculate the customers who purchased for three months in a row using the formula below.
All I have added is a different calculation that jumps back two months, instead of one.
After that, I’ve added an INTERSECT function inside another INTERSECT function. So, it will not only evaluate the customers for the current month and it’s purchase history last month. It will also check if the particular customer has also purchased 2 months ago.
To add this data into your table, simply drag the Customers 3M In A Row formula into the table.
You’ll see in the bottom that there’s a total of 45 customers who purchased for three months in a row. This is quite an intensive insight that is very useful.
As mentioned earlier, INTERSECT is a table function and it can be used in many different ways.
The focus with this tutorial is for you to see how you can utilize it in a measure and in various ways within a measure. That’s how I think this can be used in a very efficient way to run some exceptionally compelling analysis.
How to use Snapchat’s Gender Swap feature?
People on social media always look for ways to gain attention, have fun and Snapchat offers all the tools. From putting puppy ears on your face to terrifyingly swapping your face Snapchat provides various lens filters. The latest addition to this range of filters is, Snapchat’s new gender swapping feature. Of late, people are using gender swapping feature to merge traits with the opposite sex and create a buzz.
These two new Snapchat’s filters make you look feminine and vice versa. Where the “male” filter adds facial hair, shorten your hair and adds a stronger jawline, “female” filter removes beard replacing it with smooth skin, makeup, and long hair.
Here’s how to use Snapchat’s gender-swapping filters.
Also Read: How To Find Someone On Snapchat Without Username Or NumberHow to find and use Snapchat’s gender-swapping filter?
2. Ensure you are using the front-facing camera, if not tap on the rectangular arrows in the top corner to enable the front camera.
3. Next, to bring all the installed lenses to tap on the face icon next to the shutter button at the bottom.
4. Here, you’ll be able to see a wide range of filters. Snapchat’s new gender swapping filter will be within the first five options. For women, select the filter with a beard and for men select the filter with makeup. Both these filters are next to one another.
5.Once you have used the filter, the screen will shine. If you are ready, snap the picture.
Using these simple steps, you can now gender swap your photos and share it with your friends and family.But why this filter?
The app that used to be hugely popular suddenly became irrelevant.
It seems to fight this decreasing popularity; Snapchat was looking for something that would gain users attention. And this new gender-swap lens filter is the answer to it.
Although, with this Snapchat is back.
Moreover, the gender swap feature reflects the company’s thought process and its biases. As in Snapchat’s world, an attractive woman apparently means one with long hair, thick and long lashes. While being a man means having short hair, thick eyebrows, square jawline and most importantly a beard. Isn’t it somewhat ironic that an app that encourages you to play with gender has such a binary view of it?
To some extent, this feature is great, as it has brought to light the type of abuse women had to face on dating apps. As men posing as female have started to receive a vulgar message from male suitors.
For some, this can be just an exaggeration but we cannot forget while gender-swapping online might be just for fun, but people still get killed for doing it in real life.Quick Reaction:
About the author
After having an extensive discussion about the query editor, it’s time to move all that data into a Power BI report through data modeling. You may watch the full video of this tutorial at the bottom of this blog.
Data modeling allows you to connect different data tables in your Power BI report by creating relationships between them.
My core data model consists of all the tables I fixed in the query editor. This includes my Customers table, Locations table, Products table, etc.
Of course, this doesn’t mean that I won’t be going back into the query editor once I start working on data modeling. I would definitely be coming back into it a lot, especially if I need to make additional transformations or if I need to bring in new data depending on what my reports require.
The process of applying the queries into my Power BI model might take some time, depending on the amount of data I have.
But once the application is done, I’m going to end up on a fresh canvas where I can start creating my analysis.
Some people may jump straight into this part. But what I usually do is check the relationships built around the data I worked on when I was in the query editor.
This is the modeling area, which I can access through this particular icon here.
If you have no Power BI experience and were previously working on Excel, this will be completely unfamiliar to you. It’s important that you understand this part because it is crucial in developing anything within Power BI.
This is where I can make sure that the relationships across my data are set up in an optimal manner. Otherwise, it will be harder to get any calculation or analysis done correctly.
The relationships are represented by these lines and arrows running across the data tables.
Power BI normally guesses the relationships among the different tables automatically. Unfortunately, Power BI gets this part wrong most of the time.
So I usually start off by deleting these existing relationships, especially when I’m 100% unsure if the default relationships Power BI has placed make sense.
In Excel, you would normally have one huge file with hundreds of columns. But data modeling within Power BI is different.
Here, for example, I have a core set of information, and then I have separate supporting tables that have filtering information within them. So I end up with different tables with different data groups in each one.
This is the critical part in data modeling – identifying whether each table is a lookup table or a fact table. It’s important to understand what these two types of tables do so that you can understand what kind of relationships you can draw through them.
A fact table carries all the transactions, like in this sales table.
On the other hand, a lookup table carries filtering information.
Once I’ve identified where my tables belong, I organize them. I like lining up my lookup tables here on top in a single row.
As for my fact table, I like putting it below.
Of course, some people might do it differently. But this is the best practice I want to share because I have a philosophy of keeping things as simple as possible.
I layer these tables like this because I want to visualize how the relationships go. I call this a waterfall of filters. This way, I have my lookup tables on top sending filtering information down into the raw data that I’m working with.
This is very basic stuff, but it’s crucial that you master this because it can make or break your calculations later on.
Understanding the basics of data modeling helps you make sure you’re getting the right results in your reports. It will save you the frustration of trying to find the root cause of errors that might result from the wrong relationships.
All the best,
Jordan Koene is a SEJ Summit veteran, having spoke at a few of our search marketing conferences last year. This year, we’re happy to have him at SEJ Summit Chicago, speaking on how to improve search visibility.
Jordan’s insights below are always enlightening and cover everything from moving past a plateau to how e-commerce SEO is different from other channels.Want to see Jordan and other speakers from The Daily Dot, Sapient Nitro, Google, and more? Chicago Early Bird tickets are on sale now! Your SEJ Summit presentation is titled Surviving the Search Plateau: 3 Tactics to Bring Your Website’s SEO Visibility to New Heights. How do you determine if you are in an SEO plateau? What signs would you look for? One of the examples you give for breaking free from the plateau is by igniting your content. Does that mean blending content marketing into your SEO strategy?
That can be a piece of it, though that can take a lot of time and money. From a search perspective, the low-hanging fruit is to simply refresh the content you already have with new material, or by making minor changes. Like layering a cake, you can build on top of your old content with structured data or info to create something interesting and new. Minor changes can bring big rewards.I did a little bit of stalking and saw you are interested in wearable technology. What is your favorite wearable piece of tech—either already on the market or coming soon? You have a background in e-commerce, having worked for eBay in the past. How does SEO differ for big e-commerce brands versus, say, a service based brand.
E-commerce has this mentality of short-term gains: everything is about making short-term progress in a competitive ecosystem, especially here in the US. For that reason, a good deal of the decision making is relatively short-sighted, and you might not see them invest in long-term plays like you would for a news or media outlet. Service-based companies are more focused on having an online to offline presence since they essentially evolved from the big directory business.
A lot of service companies are moving into a transactional service model to marry in e-commerce behaviors, like Yelp, which now offers a bidding service for consumers looking to nail down a service for a particular price. In that way, they’re becoming more similar as more companies adopt that model.Bonus Question: What was the last book you read?
I’m currently starting Shoe Dog by Phil Knight. I’ve been interested in selling in an era where e-commerce didn’t exist, and was looking for parallels into how shopping is changing today. People like Phil Knight are pioneers who broke down lots of barriers in the market to rise to success, but it’s interesting to dig into how much of his success was based on societal changes at the time – and how societal changes today might reflect market changes to come.Thanks Jordan! Phil Knight is a legend in sports & business. Along the same line, I’m hooked on the 30 For 30 documentaries– super inspiring sports stories. See you in Chicago!
Don’t forget, you can buy your ticket for our SEJ Summit Chicago conference, taking place June 23 at the Navy Pier. Or, come see us in NYC Nov. 2nd!
The path to 5G
Before we look at LTE Advanced Pro in some detail, let’s understand exactly where this all aims to end up. The goal is to continue to evolve the current LTE standard towards reaching the 5G specifications. The standard looking to become a rather large, all-encompassing wireless communication system that not only caters for faster data speeds, but also supports many more devices online at the same time with greatly reduced latency.
Although there currently isn’t a definitive standard for a 5G technology just yet, the groups working on the early trials have defined a number of key requirements going forward. Here are some of the most important ones:
1Gbps to 10Gbps connections for peak data rates
100Mbps cell edge data rate (mobile data speeds)
1 millisecond end-to-end latency
1000x bandwidth per unit area
10-100x number of connected devices
90% reduction in network energy usage
Improved coverage, with a perception of 100% coverage
ARM announces its Cortex-R8, destined for future 5G modems
Other improvements to the standard include more efficient channel encoding, a new FDD/TDD data frame structure designed to reduce latency, and adaptive carrier upload/download allocation for traffic offloading and optimization. Additional antennas can also be deployed at base stations with enhanced MIMO for additional network coverage.
When it comes to the lower power device support and superior connectivity, LTE-M and NB-IOT technologies encompassed in LTE-A Pro will offer lower speed, narrow band access for low power devices. The aim is to reduce power consumption and costs, while allowing for high node density. Low data rate of just a few 100 kbps and much slower latencies should keep power usage down for these devices, while high bandwidth networking is reserved for our more powerful gadgets and other connected devices.
Release 14 of LTE-A Pro also aims to also coalesce vehicle-to-vehicle (LTE V2X) and device-to-device communications, convergent TV services, and location/proximity aware mobile devices for social networking and emergency services. It really is a huge standard to cover virtually any form of communication that you can think of.
If all this techno-jargon is a little off-putting, Qualcomm has put together a rather handy video that helps to explain a lot of these fundamental points.Wrap Up
The long and the short of it is that LTE Advanced Pro aims to vastly increase the data speeds and bandwidth available for mobile communication by streaming and collecting data through a wider range of technologies. Not only that, but the technology wants to bring a much wider range of connected devices and platforms all under a single standard. This could enable brand new ways of communicating with each other and open up doors to innovative new products and markets. All of which is a precursor for next-generation 5G technologies.
We have already seen trials and modems offering support for some of the components of LTE Advanced Pro, but major roll-outs aren’t expected to begin hitting markets for a year or more yet. Even then, different countries and carriers will begin rolling out their own services in their own time, so the road to 5G is going to be very gradual. Still, now we know what’s heading our way.
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