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Question: 77
The kafka connector creates one pipe for each partition in a Kafka topic.
Answer: A
The connector creates one pipe for each partition in a Kafka topic. The format of the pipe name is:
Question: 78
Secure views cannot take advantage of the internal optimizations which require access to the underlying data in the
base tables for the view.
Answer: A
Some of the internal optimizations for views require access to the underlying data in the base tables for the view. This
access might allow data that is hidden from users of the view to be exposed through user code, such as user-defined
functions, or other programmatic methods. Secure views do not utilize these optimizations, ensuring that users have no
access to the underlying data.
Question: 79
You have created a table as below
What data type SNOWFLAKE will assign to column NAME?
Answer: C
Try it yourself
Execute the below commands
Question: 80
Snowflake has row level security
Answer: A
The below is an old Explanation:
Currently row level security is not available in Snowflake. There is a work around to achieve this using
views and permissions.
New Explanation:
Snowflake has introduced row level security now. However it is still in preview feature. Please read the
below link
Question: 81
To convert JSON null value to SQL null value, you will use
Answer: C
The NULL_IF function in Snowflake is used to compare two expressions, and if they are equivalent, a SQL NULL
value is returned. However, when dealing with JSON data and the goal is to convert JSON null values to SQL NULL
values during ingestion, you would use the STRIP_NULL_VALUE file format option. This option can be set when
creating or altering a file format used for loading JSON data, and it will remove JSON fields with null values from the
ingested data, effectively treating them as SQL NULL values.
Question: 82
Following objects can be cloned in snowflake
A. Permanent table
B. Transient table
C. Temporary table
D. External tables
E. Internal stages
Answer: C
In Snowflake, the ability to clone objects is an important feature for quickly duplicating the schema and data of various
database objects. Here's the capability of cloning the listed objects:
A. Permanent table
Yes, permanent tables can be cloned in Snowflake. The clone includes the data and schema of the table at the time of
B. Transient table
Yes, transient tables can also be cloned. Similar to permanent tables, the clone includes the data and schema of the
transient table.
C. Temporary table
No, temporary tables cannot be cloned in Snowflake. Temporary tables are session-specific and are dropped
automatically when the session ends.
D. External tables
No, external tables cannot be directly cloned in Snowflake. External tables point to data stored outside of Snowflake,
typically in an external stage, and their metadata can be replicated or recreated, but not cloned in the same way as
internal tables.
E. Internal stages
Yes, internal stages can be cloned in Snowflake. Cloning an internal stage creates a new stage with the same file
format and other settings.
Therefore, the objects that can be cloned in Snowflake are:
A. Permanent table
B. Transient table
E. Internal stages
Question: 83
What will the below query return
A. The top 10 highest grades
B. The 10 lowest grades
C. Non-deterministic list of 10 grades
Answer: C
An ORDER BY clause is not required; however, without an ORDER BY clause, the results are non-deterministic
because results within a result set are not necessarily in any particular order. To control the results returned, use an
ORDER BY clause.
n must be a non-negative integer constant.
Question: 84
You need to choose a high cardinality column for the clustering key
Answer: A
Choosing a high cardinality column for the clustering key can be beneficial, especially if the column is frequently used
in filters, join conditions, or range queries. High cardinality means that the column has a large number of unique
values, which can help Snowflake organize the data in micro-partitions more efficiently for these types of operations.
However, it's important to consider the overall access patterns and query performance when designing clustering keys,
as the best choice may vary depending on the specific use case.
Question: 85
Below are the rest APIs provided by Snowpipe
A. insertFiles
B. insertReport
C. loadData
Answer: A
A. insertFiles: This is a REST API provided by Snowpipe in Snowflake. The insertFiles API endpoint is used to tell
Snowpipe to load data from files that you stage in a cloud storage service. You can use this API after you've staged
your files to begin the data load process.
B. insertReport: This is not a standard REST API provided by Snowpipe in Snowflake. There is no insertReport API
endpoint in the Snowpipe REST API documentation.
C. loadData: This is not a standard REST API provided by Snowpipe in Snowflake. The typical REST API command
used to load data is insertFiles, as mentioned above.
The correct answer is:
A. insertFiles
Question: 86
Every Snowflake table loaded by the Kafka connector has a schema consisting of two VARIANT columns.
Which are those?
Answer: A,B
Schema of syllabus for Kafka Topics
Every Snowflake table loaded by the Kafka connector has a schema consisting of two VARIANT columns:
Question: 87
Who can provide permission to EXECUTE TASK?
Answer: A
If the role does not have the EXECUTE TASK privilege, assign the privilege as an account administrator (user with
the ACCOUNTADMIN role), e.g.:
use role accountadmin;
grant execute task on account to role ; k-owner
Question: 88
You have created a TASK in snowflake.
How will you resume it?
A. No need to resume, the creation operation automatically enables the task
Answer: B
It is important to remember that a Task that has just been created will be suspended by default. It is necessary to
manually enable this task by "altering" the task as follows:
Question: 89
What will happen if you try to ALTER a COLUMN(which has NULL values) to set it to NOT NULL
A. An error is returned and no changes are applied to the column
B. Snowflake automatically assigns a default value and let the change happen
C. Snowflake drops the row and let the change happen
Answer: A
When setting a column to NOT NULL, if the column contains NULL values, an error is returned and no
changes are applied to the column.
Question: 90
While choosing a cluster key, what is recommended by snowflake?
A. Cluster columns that are most actively used in selective filters
B. If there is room for additional cluster keys, then consider columns frequently used in join predicates
C. Choose a key with high cardinality
Answer: A,B
Snowflake recommends prioritizing keys in the order below:
Cluster columns that are most actively used in selective filters. For many fact tables involved in date-based queries (for
example "WHERE invoice_date > x AND invoice date <= y"), choosing the date column is a good idea. For event
tables, event type might be a good choice, if there are a large number of different event types. (If your table has only a
small number of different event types, then see the comments on cardinality below before choosing an event column as
a clustering key.)
If there is room for additional cluster keys, then consider columns frequently used in join predicates, for example
"FROM table1 JOIN table2 ON table2.column_A = table1.column_B".
Question: 91
You have create a task as below
SCHEDULE = '5 minute'
INSERT INTO mytable1(id,name) SELECT id, name FROM mystream WHERE METADATA$ACTION =
Which statement is true below?
A. If SYSTEM$STREAM_HAS_DATA returns false, the task will be skipped
B. If SYSTEM$STREAM_HAS_DATA returns false, the task will still run
C. If SYSTEM$STREAM_HAS_DATA returns false, the task will go to suspended mode
Answer: A
Indicates whether a specified stream contains change tracking data. Used to skip the current task run if the stream
contains no change data.
If the result is FALSE, then the task does not run.
Question: 92
How do you validate the data that is unloaded using COPY INTO command
A. After unloading, load the data into a relational table and validate the rows
B. Load the data into a CSV file to validate the rows
C. Use validation_mode='RETURN_ROWS'; with COPY command
Answer: C
Validating Data to be Unloaded (from a Query)
Execute COPY in validation mode to return the result of a query and view the data that will be unloaded from the
orderstiny table if COPY is executed in normal mode: copy into @my_stage
from (select * from orderstiny limit 5)
validation_mode='RETURN_ROWS'; rom-a-
Question: 93
Which of the below operations are allowed on an inbound share data?
Answer: A,D,E
This is a trick Question:) remember a share is read only, so you can only select data from a share Important
All database objects shared between accounts are read-only (i.e. the objects cannot be modified or deleted, including
adding or modifying table data).
Question: 94
Data sharing is supported only between provider and consumer accounts in same region
Answer: B
please read the below link
Question: 95
When would you usually consider to add clustering key to a table
A. The performance of the query has deteriorated over a period of time.
B. The number of users querying the table has increased
C. it is a multi-terabyte size table
D. The table has more than 20 columns
Answer: B
A. The performance of the query has deteriorated over a period of time.
Clustering keys in Snowflake are used to optimize the arrangement of data in a table's micro-partitions. Adding a
clustering key can help Excellerate the performance of queries that have become slower over time, especially if this
deterioration is due to table growth and suboptimal micro-partition pruning during query execution. This can happen
as data becomes more spread out across micro-partitions, leading to larger scans during query execution.
Options B, C, and D may not necessarily justify the need for a clustering key:
B. The number of users querying the table has increased: An increase in the number of users does not inherently
require a clustering key. If performance issues arise due to concurrency, other features such as scaling the warehouse
or using result caching may be more appropriate.
C. It is a multi-terabyte size table: While large tables could benefit from clustering keys, the size of the table alone
isn't the sole reason to add a clustering key. It would be more about the access patterns, such as frequent filtering on
certain columns, that would make a clustering key beneficial.
D. The table has more than 20 columns: The number of columns in a table does not directly impact the need for a
clustering key. The decision to add a clustering key should be based on how the data is accessed and queried, not on
the column count.
Therefore, adding a clustering key is most commonly considered to address specific performance issues related to data
retrieval patterns, not just the size of the table, the number of users, or the number of columns.
Question: 96
You are a snowflake architect in an organization. The business team came to to deploy an use case which requires you
to load some data which they can visualize through tableau. Everyday new data comes in and the old data is no longer
What type of table you will use in this case to optimize cost
Answer: B
For the given use case, where new data comes in every day and the old data is no longer required, a temporary table
would be a cost-effective option. Temporary tables in Snowflake are session-specific and are automatically dropped at
the end of the session. If the business team's visualization needs in Tableau are only for the duration of a session or a
day, and there is no need to persist the old data, then temporary tables can be used to store the data for that day's
session. This approach ensures that you're not incurring storage costs for data that is no longer needed.
If, however, the data needs to persist beyond a single session but still does not require long-term storage, a transient
table could be considered. Transient tables are similar to permanent tables but have lower data retention guarantees
and incur lower storage costs. They are suitable for scenarios where data is needed for more than just the duration of a
session but does not need the durability and retention of a permanent table.
Permanent tables are meant for data that needs to persist indefinitely and be highly durable, with full data retention
features of Snowflake, which seems more than necessary for the use case described.

SnowFlake Certification basics - BingNews Search results SnowFlake Certification basics - BingNews Nature Nuggets: The architecture of a snowflake

“It’s too early,” said the character Lucy Van Pelt in “A Charlie Brown Christmas.” “I never eat December snowflakes. I always wait until January.”

A bull elk enjoys catching snowflakes on his tongue during a spring snowstorm in Estes Park, Colorado. (Dawn Wilson Photography)

Dawn Wilson Photography

A bull elk enjoys catching snowflakes on his tongue during a spring snowstorm in Estes Park, Colorado. (Dawn Wilson Photography)

Well, here we are in January and a string of snowstorms is predicted to drop several inches over the next ten days. Time to enjoy those snowflakes.

As the snow falls, the curious mind may wonder, “How do all of those flakes form?”

Snow is frozen water. Water is made up of two hydrogen atoms and one oxygen atom, and thus creating the chemical symbol of H2O for water. It is the same for snowflakes.

These three atoms naturally and always align into a V-shape to create the water molecule.

An American avocet forages for aquatic bugs during a spring snowstorm in the Fish Creek Arm of Lake Estes in Estes Park, Colorado. (Dawn Wilson Photography)

Dawn Wilson Photography

An American avocet forages for aquatic bugs during a spring snowstorm in the Fish Creek Arm of Lake Estes in Estes Park, Colorado. (Dawn Wilson Photography)

But there is more to making a snowflake than just frozen water.

According to the National Oceanic and Atmospheric Administration, the beginnings of a snowflake include a piece of pollen or dust in the sky. When a very cold water droplet freezes onto this particle, an ice crystal forms.

As the crystal falls to the ground, additional ice crystals attach to it and begin to create the snowflake. Each of those crystals maintain the V-shape alignment of the atoms mentioned above and form a hexagon as they continue to evenly attach to the flake.

Because of this V-shaped alignment, snowflakes always have six sides. As the flake continues to fall, more crystals will attach but always in the V-shape, six-sided pattern, creating a larger hexagon shape rather than an unbalanced random shape. This process is called “crystallization.”

NOAA further explains that it is the temperature at which the crystal forms that creates the basic shape of the snowflake. The amount of humidity in the air also plays a part in the appearance of the flake. Long, needle-like crystals form at 23 degrees Fahrenheit while very flat, plate-like crystals form at 5 degrees Fahrenheit.

As a result of this combination of types of particles, amount of moisture in the air, rate of falling and temperature, no two snowflakes are ever alike because no two combinations of these factors are ever the same, creating one-of-a-kind prisms, needles, plates, columns and lacy patterns.

A snowy scene in Rocky Mountain National Park where billions of flakes blanket the landscape. (Dawn Wilson Photography)

Dawn Wilson Photography

A snowy scene in Rocky Mountain National Park where billions of flakes blanket the landscape. (Dawn Wilson Photography)

Here are some other unique features about snowflakes to ponder as you enjoy a few of the January flakes.

A snowflake falls through the air to the ground at a rate of one to six feet per second. The rate is dependent upon size and shape of the flake.

According to Tom Skilling, chief meteorologist at Chicago’s WGN-TV, snowflakes start their descent at about 10,000 feet in the atmosphere in a typical winter storm. Using a fall rate of 3.5 feet per second, the flake would take about 45 minutes to reach the ground.

Of course, that is in Chicago, where the city sits at an elevation of 597 feet. In Estes Park, where the ground is much closer to 10,000 feet, the time for that flake to reach the ground would be considerably shorter.

According to Met Office, the national meteorological office in the United Kingdom, snowflakes fall at a rate of 1 to 4 mph. They further explain that supercooled water may fall as fast as 9 mph while most flakes fall at a rate of 1.5 mph. They too state it takes about an hour for a flake to fall to the ground.

Snow is not white. Although our eyes see it that way, the flakes are actually clear. The ice crystals are not completely transparent, however, so light diffuses through the crystals in the whole spectrum of colors, creating the appearance of white.

According to NOAA, the snow to rain ratio is 10 to 1, generally. There is actually much more involved in the simple statement of how much water it takes to make one inch of snow, including temperature, wind speeds and humidity levels. The general rule of thumb is that 0.1 inches of water creates one inch of snow.

With those facts in mind, take a look at a few of the fresh flakes this week to see if you can spot the hexagon shape, find the piece of pollen or see how the crystals are clear. Or just have fun playing in the piles of flakes.

Thu, 04 Jan 2024 08:06:00 -0600 Dawn Wilson en-US text/html
Snowflake bucks downgrade even as analyst says AI talk is all talk (update) No result found, try new keyword!Snowflake (SNOW) fell on Thursday amid a downgrade from Monness, Crespi, Hardt, which called the stock overvalued and dismissed its AI talk. Read for more. Thu, 04 Jan 2024 04:06:38 -0600 en-us text/html Master Gardener Basic Training

program details

Our main objective is to train volunteers to assist Purdue Extension with home horticulture education in local communities. Purdue EMG’s receive training in horticulture to equip them to fulfill  this educational role through volunteering in a variety of projects approved by their local EMG County Coordinator (Purdue Extension Educator). The requirements for Purdue EMG certification include acceptance into the training through an application and screening process, payment of registration fee, completion of the EMG Basic Training which includes passing the open-book final exam with a score of 70% or higher, and contributing at least 40 hours of volunteer service approved by the local EMG County Coordinator within two years. Purdue Extension Master Gardeners are also required to complete at least 12 volunteer and 6 continuing education hours every year in order to stay active. 

This class runs from August 31st to November 30th on Thursday nights from 6pm to 9pm. We are currently accepting applications for this class.

Please note that we will meet on Tuesday, November 21st for the week of Thanksgiving.

  1. Those interested submit their completed EMG-1 application.
  2. Conduct an ID check to verify identity (Available via Zoom)
  3. Consent to a standard volunteer background check (handled by our office)
  4. Complete the final registration link via CVENT (this is where the course fee is payed)


• $183.00 for an individual registration with print version of Purdue EMG Manual


Limited to the first 35 to complete registration

1) Complete this application and submit to Carey Grable


2)  After your application is received and  approved, you will be contacted to complete registration and payment.


Note:  Purdue is committed to making all programs accessible to participants. If you require auxiliary aids or services, or if you have other program-related concerns, please contact Carey Grable ( at least 2 weeks prior to the program.

To learn more about the Purdue Extension Master Gardener Program, visit

Sat, 22 Jul 2023 03:18:00 -0500 en text/html
How SuperDuperDB delivers an easy entry to AI apps

Numerous observers have predicted that 2024 will be the year enterprises turn generative AI such as OpenAI's GPT-4 into genuine corporate applications. Most likely, such applications will begin with the simplest kinds of infrastructure, stringing together a large language model such as GPT-4 with some basic data management.

Enterprise apps will start with simple tasks such as searching through text or images to find the match to a natural-language search.

Also: Pinecone's CEO is on a quest to give AI something like knowledge

A perfect candidate to make that happen is a Python library called SuperDuperDB, created by the venture capital-backed company of the same name, founded this year. 

SuperDuperDB is not a database but an interface that sits between a database such as MongoDB or Snowflake and a large language model or other GenAI program.

That interface layer makes it simple to perform several very basic operations on corporate data. Using natural language queries in a chat prompt, one can query an existing corporate data set -- such as documents -- more extensively than is possible with a typical keyword search. One can upload images of, say, products to an image database and then query that database by showing an image and looking for a match.

Likewise, moments in videos can be retrieved from an archive of videos, by typing themes or features. Records of voice messages can be searched as a text transcript, making a basic voicemail assistant. 

The technology also has uses for data scientists and machine learning engineers who want to refine AI programs using proprietary corporate data. 

Also: Microsoft's GitHub Copilot pursues the absolute 'time to value' of AI in programming

For example, to "fine-tune" an AI program such as an image recognition model, one has to hook up an existing database of images to the machine learning program. The challenge is how to get the image data into and out of the machine learning program, and how to define variables of the training process, such as the loss to be minimized. SuperDuperDB offers simple function calls to simplify all those things.

A key aspect of many of those functions is to convert different data types -- text, image, video, audio -- into vectors, strings of numbers that can be compared against one another. Doing so allows SuperDuperDB to perform "similarity search," where the vector of a text phrase, for example, is compared to a database full of voicemail transcripts to retrieve the message most closely matching the query. 

Mind you, SuperDuperDB is not a vector database like Pinecone, a commercial program. It's a simpler form of organizing vectors called a "vector index."

Also: Pinecone's CEO is on a quest to give AI something like knowledge

The SuperDuperDB program, which is open-source, is installed like a typical Python installation from the command line or loaded as a pre-built Docker container. 

The first step to working with SuperDuperDB can either be setting up a data store from scratch, or working with an external data store. In either case, you'll want to have a data repository such as MongoDB or a SQL-based database. 

SuperDuperDB handles all data, including newly created data and data fetched from the database, via what it calls an "encoder," which lets the programmer define data types. These encoded types -- text, audio, image, video, etc. -- can be stored in MongoDB as "documents" or in SQL-based databases as a table schema. It's also possible to store very large data items, such as video files, in local storage when they exceed the capacity of either MongoDB or the SQL database.

Also: Bill Gates predicts a 'massive technology boom' from AI coming soon

Once a data set is chosen or created, neural net models can be imported from libraries such as SciKit-Learn or one can use a very basic built-in inventory of neural nets such as the Transformer, the original large language model. One can also call APIs from commercial services such as OpenAI and Anthropic. The core function of having the model make predictions is done with a simple call to a ".predict" function built into SuperDuperDB.

When working with a large language model or an image model like Stable Diffusion or Dall-E, the neural net will seek to retrieve answers from the database by performing the vector similarity search. That's as simple as calling a ".like" function and passing it the query string.

It's possible to make more complex apps by assembling multiple stages of functionality with SuperDuperDB, such as using similarity search to retrieve items from a database and then passing those items to a classifier neural net. 

The company has added functions that make an app more of a production system. They include a service called Listeners that re-run predictions whenever the underlying database is updated. Various functions in SuperDuperDB can also be run as separate daemons to Excellerate performance.

Also: How LangChain turns GenAI into a genuinely useful assistant

This year will witness a great deal of evolution in programs such as SuperDuperDB, making them more robust still for production purposes. You can expect SuperDuperDB to evolve alongside other important emerging infrastructures such as the LangChain framework and commercial tools such as the Pinecone vector database. 

While there's a lot of ambitious talk about enterprise use of GenAI, it probably starts right here, with the kinds of humble tools that can be picked up by the individual programmer.  

If you'd like to get a quick feel for SuperDuperDB, head over to the demo on the company's Web site.

Tue, 02 Jan 2024 17:16:00 -0600 en text/html
Aimore Technologies, The Leading Software Training Institute In Chennai, Launches Snowflake Training
(MENAFN- NewsVoir) Chennai, Tamil Nadu, India

Aimore Technologies , a dynamic software training institute in Chennai at the forefront of new-age tech upskilling and reskilling programs, proudly announces the launch of its latest initiative – the Snowflake Training Certification Course. In response to the increasing demand for skilled professionals in the tech industry, the Chennai-based company aims to deliver domain-specialized, tailored training modules and live projects. These offerings are designed to equip learners with the expertise needed to secure lucrative job opportunities in the ever-evolving technology market.

This initiative comes at a crucial time, given the remarkable expansion within Snowflake's industry, having reported an impressive 54% year-over-year growth in product revenue, reaching a substantial $555.3 million. Notably, Snowflake secured the top spot on the 2023 Fortune Future 50 List, underscoring its potential for enduring long-term growth, particularly in the age of generative AI.

Snowflake is increasingly gaining industry recognition, exemplified by Deloitte being named Global Partner of the Year at Snowflake's annual user conference, Snowflake Summit 2023. This marks the third consecutive year Deloitte has received this honour, highlighting the growing importance of Snowflake technology in the data cloud space.

Product Revenue from 2022 to 2023 and Projected Growth for 2024

The graph above shows the significant increase in product revenue from 2022 to 2023 and projected growth for 2024. Additionally, it provides insights into the total customer base and the subset of customers contributing over $1 million in revenue for the year 2023.

Key observations include:

    Fourth Quarter Fiscal 2023 Product Revenue: $555.3 million

    Year-Over-Year Growth in Product Revenue: 54%

    Total Customers: 7,828

    Customers with Over $1 Million Revenue: 330

    Fiscal 2024 Product Revenue Growth Projection: 40%

This industry surge is a clear indicator of the growing demand for skilled professionals in Snowflake technologies. The rise of Snowflake as a key player in data warehousing and cloud solutions not only boosts the technology sector but also opens up vast opportunities for educational organisations to contribute to shaping the future of data-driven industries.

India, a hub for engineering students, annually produces 1.5 million graduates in the field. Despite this substantial number, only a fraction possess a comprehensive understanding of Snowflake. This deficiency presents challenges for the country's rapidly expanding startups and businesses, which increasingly demand developers with the requisite skill sets.

Snowflake, a cutting-edge data warehousing technology, is intricately crafted to leverage the flexibility of the cloud. With its potential fully harnessed, Snowflake demonstrates unique capabilities, such as infinite and immediate scalability, positioning itself as a potentially ultimate data warehouse solution.

Aimore Technologies, in response to market demands, has meticulously developed the entire module for the Snowflake training course in Chennai . A key differentiator lies in the program's emphasis on practical training over a theoretical approach. Distinguished professionals boasting years of expertise serve as trainers for this initiative. Notably, the course's domain specialisation feature enables working professionals to elevate their careers by mastering real-time capstone projects within their specific domains.

Commenting on the recent launch of the course, a spokesperson for Aimore Technologies stated, "We are committed to delivering personalised learning plans tailored to master specific domains or job roles. Our program encompasses 55 hours of instructor-led training, coupled with direct sessions to promptly address doubts. Students have the flexibility to choose batches that align with their requirements, opting for either direct or virtual training based on their learning convenience. The course ensures practical experience through lab sessions, simulating real-world scenarios. Candidates benefit from extensive hands-on training, culminating in a 100% placement track record at top multinational corporations."

Aimore Technologies has outlined plans to broaden its reach by establishing additional specialised training hubs across India in the future. Concurrently, the company aims to augment the number of trainers across all locations. The overarching mission is to eliminate barriers to learning, ensuring widespread access to skill enhancement for students.

About Aimore Technologies
Aimore Technologies stands out as a premier software training institute in Chennai , renowned for its excellence in preparing individuals for the digital future. The institute offers specialised IT programs in pivotal domains such as Web Development, Snowflake, Software Testing, AWS, Data Science, and Python . Under the guidance of proficient trainers, students not only acquire a deep understanding of technology but also gain practical proficiency in its application. Aimore Technologies is committed to shaping individuals into adept professionals, equipping them with the skills needed to thrive in the dynamic landscape of the digital world.

To know more about Aimore Technologies and the courses they offer, visit .


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Thu, 14 Dec 2023 00:16:00 -0600 Date text/html
For Easy Winter Latte Art, A Spoon And Toothpick Are All You Need

You don't need professional barista training to make cute latte art on the coffees you drink at home. Using foamed milk and freshly poured espresso, you can create Instagram-worthy snowflakes on top of your next mug of coffee. Simply use a teaspoon to drop dots of foamed milk onto the surface of the poured crema in a star formation and connect each droplet using a toothpick or skewer to draw a milky snowflake design in your cup. You'll want to make sure the milk foam you use is finely textured and silky so that the wintery design holds its shape.

Snowflake patterns make for the kind of design that doesn't require any sort of perfect pouring pattern or fancy skills. Keep the milk droplets aligned in a circular form so that the marks you draw with either a toothpick or skewer can easily line up and it looks like a snowflake. After a few tries, your picture-perfect snowflake designs may become the talk of your household.

Read more: 26 Coffee Hacks You Need To Know For A Better Cup

cinnamon snowflake on coffee cup - ANTON URICH/Shutterstock

After you've mastered the technique of making snowflakes on top of your lattes and cappuccinos using droplets of microfoamed milk, you can try sprinkling snowflakes on top of your favorite milky coffee recipes with powdered cinnamon or cocoa. Use the handle of a spoon to help you connect up elements of your designs, or make cut-outs with parchment paper or aluminum foil that you can place gently over your coffee cups as a stencil.

Snowflake designs can provide an endless source of inspiration, and depending on how complex you'd like your latte art to be, can keep you busy as you work to perfect the shapes and styles of your latte art. In time, you may find yourself enjoying more coffee drinks at home instead of heading to the nearest coffee shop for a pretty pour. With enough practice, you may even give your neighborhood baristas some stiff latte-art skills competition.

Read the original article on Tasting Table.

Mon, 25 Dec 2023 22:30:00 -0600 en-US text/html
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