A Compact List of Snowflake Features

1. Decoupling of storage and compute in Snowflake
2. Auto-Resume, Auto-Suspend, Auto-Scale
3. Workload Separation and Concurrency
4. Snowflake Administration
5. Cloud Agnostic
6. Semi-structured Data Storage
7. Data Exchange
8. Time Travel
9. Cloning
10. Snowpark
11. Snowsight
12. Security Features
13. Snowflake Pricing

Let’s deep-dive:

1. Decoupling of storage and compute in Snowflake

Snowflake's decoupling of storage and compute features facilitates virtual warehouses and storage as separate entities. Leveraging this functionality of Snowflake, businesses can achieve greater flexibility in choosing the compute of their choice and incrementally pay for what they store and compute. Users can scale up / down or in/out based on the business SLA requirement. Scale up – Scale-out features do not require downtime and are almost instant.

2. Auto-Resume, Auto-Suspend, Auto-Scale

Snowflake's auto-resume and auto-suspend features provide minimal administration. Using auto-resume, Snowflake starts a compute cluster when a query is triggered and suspends compute clusters after a set time of inactivity. These two features ensure performance optimisation, cost management, and flexibility.

In business circumstances where more users are querying heterogeneous queries, setting up auto-scaling can help automatically expand the number of clusters from 1 to 10 at an increment of 1 based on the volume of queries sent to a compute simultaneously.

3. Workload Separation and Concurrency

Concurrency is no longer a problem for Snowflake, unlike traditional data warehouses with concurrency issues where users and processes must compete for resources. Because of Snowflake's multi-cluster architecture, concurrency is not an issue anymore.

This architecture also helps to divide workloads into their virtual warehouse and channel the traffic to each virtual warehouse (compute) by functions or departments.

4. Snowflake Administration

A data cloud as a service is provided by Snowflake (DWaas). Businesses can set up and administer a system without significant assistance from DBA or IT teams. Unlike the on-premise platforms, neither hardware commissioning nor software installation patch-update is s necessary. Snowflake manages software updates and introduces new functions and patches without downtime.

Snowflake automatically creates micro-partitioning. This feature reduces the requirement of manually indexing and clustering tables though these are available features in Snowflake.

5. Cloud Agnostic

Being a cloud-agnostic platform, Snowflake can migrate its workloads with other cloud providers. So, Snowflake is accessible on all three cloud providers: AWS, Azure, and GCP. Customers can easily integrate Snowflake into their existing cloud architecture and choose to deploy in locations preferred by their companies.

6. Semi-structured Data Storage

The requirement to manage semi-structured data, often in JSON format, gave rise to NoSQL database solutions. Data pipelines are created to extract attributes from JSON and mix them with structured data. By leveraging VARIANT, a schema on read data type, Snowflake's design enables storing structured and semi-structured data in the exact location. Both organised and semi-structured data can be stored using the VARIANT data type. Snowflake eliminates the need for data extraction pipelines by automatically analysing data, extracting properties, and saving it in a columnar format.

Snowflake can connect to staging areas like s3 bucket, Azure blob or GCP blob storage to retrieve and transform files stored in these platforms. This is regardless of the cloud Snowflake is hosted. A snowflake-managed staging area is also available. Tasks/ Streams or Snowpipe can be set to retrieve data at a scheduled time or almost instantly, respectively. Snowflake can work with CSV, JSON, XML, Avro, ORC, and Parquet file formats. Snowflake can also store metadata of unstructured data stored in the staging area.

7. Data Exchange

A wide range of data, data services, and applications are available on the Marketplace. From some of the world's top data and solution suppliers, you can find, assess, and buy data, data services, and apps through Marketplace. Direct access to data ready for querying and pre-built SaaS connections virtually eliminates the expenses and delays associated with conventional ETL operations and integration. The risk and hassle of duplicating and relocating outdated material should be avoided. Instead, you can receive automatic updates that are close to real-time and have secure access to shared, controlled, and live data.

8. Time Travel

One of the distinctive Snowflake elements is time travel. You may follow the evolution of data through time by using time travel. All accounts have access to this Snowflake feature, free and enabled by default for everyone. Additionally, this Snowflake feature allows you to retrieve a Table's historical data. At any moment throughout the previous 90 days, one can access the table's appearance.

Time travel encompasses the undrop feature. If an object has not been removed yet by the system, a dropped object can be recovered using the undrop command in Snowflake. When an object is undropped, it returns to its original condition. The option to undrop schemas or tables is also available.

9. Cloning

The clone capability allows us to quickly duplicate anything, including databases, schemas, tables, and other Snowflake objects, in almost real time. Therefore, cloning an object involves editing its metadata rather than duplicating its storage contents. You can quickly produce a clone of the whole production database for testing purposes.

10. Snowpark

With the help of the Snowpark feature, data scientists and data engineers proficient in Python, Scala, R, and Java may create and manage their codes in Snowflake. Snowpark helps to employ the computing capabilities of Snowflake to retrieve, transform, train and apply data science models on the data stored in Snowflake, which has a more apparent performance advantage,

11. Snowsight

The new Snowflake web user interface, Snowsight, replaces the traditional Snowflake SQL Worksheet and enables you to easily construct basic charts and dashboards that can be shared or explored by many users, do data validation while loading data and conduct ad-hoc data analysis. The Snowflake dashboards tool is an excellent option because it works well for individuals or small group users in an organisation who wish to generate straightforward visualisations and share information among themselves.

12. Security Features

Snowflake assures security for its users through the following methods:

• • By adding IP addresses to a whitelist, you may control network policies and limit who can access your account.
• • By supporting several authentication techniques, including federated authentication and two-factor authentication for SSO.
• • Using a hybrid approach of role-based access control and discretionary access control. In role-based access control, privileges are assigned to roles which are then transferred to users. Still, in discretionary access control, each object in the account has an owner who controls access to the object. This hybrid strategy offers a substantial level of flexibility and control.

AES 256 strong encryption is used to automatically encrypt all data, both in transit and at rest.

13. Snowflake Pricing

The advantages of Snowflake pricing are:

• • Pay for actual consumption only.
• • We can cut back on resource use to save costs.
• • Flexible payment. We can either pay on-demand or in advance (pre-purchased).
• • Scale up or down the use of cloud services, computing, and data storage automatically based on your needs.
• • There are no chances of overbuying or overprovisioning.

Optimisation of Snowflake spending through integration with innovative cost-monitoring platforms.

Snowflake stands as an ideal and popular choice because of its unique and updated features. It is also available across many data cloud providers and regions, making it accessible and suitable for all organisations. Why wait? Let’s experience Snowflake. Try now: https://beinex.com/snowflake/.

Google Cloud Platform is a Google-delivered complete set of cloud computing services. The services extend to networking, storage, application development, computing, Big Data and even more, which operate on the same cloud infrastructure used internally by Google for Gmail, YouTube, and others. What makes GCP a reliable and secure cloud infrastructure to build, test and run applications is the fact that its server has not gone down in years. IT professionals, software developers and cloud administrators can access GCP services online.

Why choose the Google Cloud Platform?

In 2022, Gartner Magic Quadrant Cloud Infrastructure and Platform services named Google as a leader for the fifth time in a row. Google Cloud Platform's global network of data centres spans multiple continents, ensuring low-latency access and redundancy for your applications and data. Therefore, GCP can be the perfect choice for organisations looking for a globally renowned cloud platform known for its wide array of services and offerings. GCP's extensive catalogue of services with unique features can be attributed to the global expansion and recognition of the platform. Some of GCP's significant services include Computing, Storage, Networking, Big Data, Cloud AI, Security and Identity Management, Management Tools, and IoT.

Besides, the following aspects also add to the reasons why GCP is a viable cloud provider for businesses:

1. Provides multi-level security to safeguard resources like assets and operating systems
2. Has a network infrastructure comprising physical, logistical, and human-resource-related elements, like wiring, routers, switches, and firewalls
3. Has proficient experts who provide support on installation and maintenance

Key Benefits of Google Cloud Platform

GCP enables customers to access computer resources located in Google's global data centres at no cost or on a pay-per-use for the services and resources used. GCP hosting plans are cost-effective compared to other platforms and offer superior features.

With features like data encryption, multi-factor authentication, and identity and access management, GCP prioritises the security of client data and applications.

Google's web-based applications provide users with complete accessibility to GCP from virtually anywhere.

GCP delivers enterprise-grade solution architectures and tech strategies to provide scalability and expedite digital transformation.

Google boasts its proprietary network infrastructure, granting users greater control over the functions of GCP. As a result, users experience seamless performance and heightened efficiency across the network.

GCP offers tools for automation, compliance and governance and a secure cloud environment to navigate challenges in cloud operations.

GCP enables organisations to harness the power of AI to automate processes, gain data-driven insights and employ machine learning for innovation.

With services like Bigtable and Cloud Storage, GCP benefits organisations in managing extensive data and facilitating real-time data processing and analysis.

Real-World Business Challenges & GCP Solutions

GCP’s suite of solutions assists organisations in tackling challenges in the dynamic business landscape effectively. Some common challenges in business and their respective GCP solutions are briefed below.

GCP equips your business with analytics tools and robust data storage to manage extensive data effectively and derive valuable insights.

With development and deployment tools like Cloud Functions and Google App Engine, GCP enables organisations to expedite development and gain a competitive edge.

GCP’s extensive global network infrastructure aids businesses by ensuring the applications reach across the world seamlessly.

With its suite of security tools for threat detection, data encryption and access and identity management, GCP safeguards data and applications with multi-level security.

In the event of unanticipated disruptions that halt business operations, GCP ensures business continuity with its backup options and disaster recovery solutions, making critical applications and data accessible.

X (formerly Twitter), eBay, PayPal, and 20th Century Fox are some of the top users who have leveraged the transformative potential of Google Cloud Platform. Being a globally recognised brand for its speed, performance, security, reliability and innovation, the Google Cloud Platform is a beacon of digital transformation for businesses navigating the challenges of the data-driven digital era. As companies venture on their journey with GCP, the prospects are endless. This partnership empowers businesses with the tools, resources, and support needed to thrive in a dynamic landscape. Whether achieving operational efficiency, reducing costs, or delivering superior customer experiences, GCP catalyses change.

What can Beinex do for you?

Beinex is now a service partner of GCP and is helping businesses advance their digital transformation endeavours by leveraging GCP’s AI capabilities, cloud infrastructure, and data analytics. Beinex offers clients expert guidance in deploying proactive solutions and using Google Cloud to make more informed data-driven decisions. This approach enables them to overcome business challenges and fosters competitiveness, efficiency, and growth. At Beinex, we deploy Google Cloud Platform as a service and the infrastructure as a service, enabling organisations to streamline access to a broader array of services and resources, resulting in cost efficiency and improved quality.

Semi-structured Formats with Snowflake Support

• • JSON
• • Avro
• • ORC
• • Parquet
• • XML

• • Variant
• • Flatten

Variant

A variant is a datatype which can hold semi-structured data in a single field. Snowflake stores semi-structured data in the column format when semi-structured data is loaded into a VARIANT column. A single row can contain other underlying data. Let’s demonstrate with the help of examples:

The stored data can be easily retrieved and structured from the above table by a simple query as below:
select
v:time::timestamp as observation_time,
v:city.id::int as city_id,
v:city.name::string as city_name,
v:city.country::string as country,
v:city.coord.lat::float as city_lat,
v:city.coord.lon::float as city_lon,
v:clouds.all::int as clouds,
(v:main.temp::float)-273.15 as temp_avg,
(v:main.temp_min::float)-273.15 as temp_min,
(v:main.temp_max::float)-273.15 as temp_max,
v:weather[0].main::string as weather,
v:weather[0].description::string as weather_desc,
v:weather[0].icon::string as weather_icon,
v:wind.deg::float as wind_dir,
v:wind.speed::float as wind_speed
from json_weather_data
Note: ‘v’ is the Field (Column) name, and the JSON tags are arranged alongside to retrieve datasets.

Flatten

Compound values are flattened into multiple rows with the use of the Snowflake Flatten Command. A tool called Snowflake FLATTEN is used to transform semi-structured data into a relational structure. Relatively complex JSON structures such as nested JSON structures can be structured with FLATTEN function in Snowflake. Here is an example of the same: The above JSON file stores a single set of conversations between two texters in a single row. If the requirement is to get every individual message as a separate row a FLATTEN function can be used to produce the following result:

Here is the query to generate the above table from semi-structured data:

Summing Up

The ability of Snowflake’s assistance is undeniable. It aids you to make better decisions and offers a better overall experience when attempting to get the most out of your data, through features like Flatten and Variant. If you want to be a part of Snowflake’s incredible platform, let us help you. Beinex’s partnership with Snowflake enables us to offer you advanced features like automated tuning and elastic computing, along with analytics modernization services, to help your organisation realise exponential Return on Investment.

Why is Data Preparation Important?

Imagine building a house on a foundation of sand. No matter how impressive the blueprints or construction materials, the structure will be unstable. The same principle applies to data analysis. Inaccurate or incomplete data leads to flawed insights and potentially disastrous business decisions.
Here's how meticulous data preparation benefits organizations:

The Data Preparation Journey: A Step-by-Step Guide

While the specific steps may vary depending on the project, a typical data preparation process involves:

1. Acquiring Data: This involves identifying the necessary data, gathering it from various sources (databases, spreadsheets, etc.), and establishing secure, consistent access.
2. Exploring Data: Understanding the data's structure and quality is crucial. Analysts use data profiling techniques and visual analytics to analyze data distribution, identify missing values, and uncover potential anomalies.
3. Cleansing Data: This is where the magic happens – correcting errors, removing duplicates and outliers, and filling in missing data points to ensure data integrity.
4. Transforming Data: Data may need formatting, restructuring, or aggregation to be suitable for the intended analysis. This could involve converting date formats, pivoting tables, or calculating new variables.

Data Preparation for the Age of Big Data and Machine Learning

The rise of Big Data and machine learning has further amplified the significance of data preparation. Machine learning algorithms rely heavily on vast amounts of clean, structured data to learn and make accurate predictions.
The Challenge: Extracting value from Big Data often involves integrating data from diverse sources, each with its own structure and quality issues. Traditional data preparation methods become time-consuming and inefficient when dealing with such massive datasets.
The Solution: Modern data preparation tools like Alteryx offer a solution.

The Power of Alteryx Data Preparation

The Alteryx Analytics Automation Platform streamlines the entire data preparation process, empowering a wide range of users – data analysts, data scientists, and even citizen data scientists – to transform raw data into actionable insights. Here's how Alteryx tackles the data preparation challenge:

Key Alteryx Features for Data Preparation:

Ready to Experience the Beinex -Alteryx Advantage?

Beinex’s premier partnership with Alteryx helps us enable business users to perform mundane tasks of manual data cleansing and transformation in just minutes by automating the process in a simple visual workflow that also covers advanced and predictive analytics. Thousands of organizations globally use Alteryx to deliver quick wins and high-impact business outcomes. Beinex's Alteryx consulting services amplify the transformative potential, providing tailored expertise to ensure maximum value extraction from Alteryx's powerful capabilities.

Here is a list of a few popular business intelligence tools companies use to gain insights:

1.Sisense: Leading Cloud Analytics Platform

Sisense is one of those data analytics and business intelligence tools known for its efficiency and easy-to-use quality. It enables anyone within an organisation to manage massive and intricate datasets and analyse and visualise data without any outsourcing. It also combines data from various sources, such as Adwords, Google Analytics, and Salesforce. The in-chip technology helps it to process data faster than any other tool. Gartner, G2, and Dresner have recognised Sisense as a leading cloud analytics platform.

2.SAP Business Intelligence: Price to the Upside

SAP Business Intelligence offers advanced analytics solutions such as machine learning, BI predictive analytics, and planning and analysis. This enterprise-level client/ server system application provides data visualisation and analytics applications, reporting and analysis, mobile analytics, and office integration.

The platform focuses heavily on Customer Experience (CX) and CRM, digital supply chain, ERP, etc. What's particularly appealing about this platform is the self-service, role-based dashboards, which allow users to create unique dashboards and applications. SAP is a robust software designed for all roles that provide many functionalities on a single platform. However, the product's complexity raises the price, so be equipped for it.

3.Datapine: Accessible to non-technical users

Datapine is a comprehensive business intelligence platform that makes the intricate process of data analytics accessible to non-technical users. Datapine's solution allows data analysts and business users to blend different data sources, perform advanced data analysis, build interactive business dashboards, and create actionable business insights by adopting a comprehensive self-service analytics approach.

4.Dundas BI: Access Multiple Data Sources in Real Time

Dundas BI is a browser-based business intelligence tool that enables users to access multiple data sources in real-time. It offers excellent visualisations in the form of tables, graphs, and charts that can be personalised and viewed on mobile devices and desktop computers. Users can easily create reports and extract specific performance metrics for analysis. Dundas aids all types of businesses and industries.

5.MicroStrategy: Fast Dashboarding in Action

MicroStrategy is a business intelligence tool for enterprises that provides powerful and fast dashboarding and data analytics, cloud solutions, and hyperintelligence. Users can use this solution to identify trends, and new possibilities, increase productivity, etc. It can be accessed via desktop or mobile and can be connected to one or more sources.

6.Yellowfin BI: No-co-Low-co Approach

Yellowfin BI is a business intelligence and analytics platform that combines visualisation, machine learning, and collaboration. It can quickly sort through massive amounts of data using intuitive filtering, and it is accessible from anywhere. This BI tool takes dashboards and visualisations to the next level by utilising a no-code/low code development environment.

7.Qlik Sense: Search & Conversational Analytics

A product of Qlik, QlikSense is a complete data analytics platform and business intelligence tool. QlikSense can be accessed from any device at any time. The user interface of QlikSense is optimised for touchscreen, which makes it a prevalent BI tool. It offers a one-of-a-kind associative analytics engine, sophisticated AI and a high-performance cloud platform, making it more attractive. An exciting feature of this platform is its Search & Conversational Analytics, enabling a faster and easier way to ask questions and discover new insights through natural language.

8.Zoho Analytics: Blend and Merge Data

Zoho Analytics is an excellent BI tool for detailed reporting and data analysis. It supports automatic data syncing and can be scheduled regularly. It quickly creates a connector and formulates meaningful reports by blending and merging data from various sources using the integration APIs. It helps to quickly identify the essential details by creating ersonalized reports and dashboards with an easy editor. It also includes a distinct commenting section in the sharing options, ideal for collaboration.

9.Microsoft Power BI: Identify Trends in Real Time

Microsoft Power BI is a web-based tool that is one of the best for data visualisation. It enables users to identify trends in real-time and includes brand new connectors that allow businesses to step up marketing campaigns. Microsoft Power BI is accessible virtually from any location as it is web-based. This tool is designed to integrate apps and deliver reports in real-time dashboards.

10.Looker: Ideal for SMEs

Looker, a data discovery app, is another business intelligence tool to watch for! This unique platform is now part of Google Cloud and integrates with any SQL database or warehouse and is ideal for startups, midsize businesses, and enterprise-grade businesses. This tool's advantages include its ease of use, useful visualisations, powerful collaboration features such as easy integration with apps, flexible sharing of data and reports via email or USL, and a dependable support system.

11.Clear Analytics: Just Need Essential Excel Skills to Use

Clear Analytics is an easy-to-use Excel-based software that can be utilised even by employees with just the essential Excel skills. It is a self-service Business Intelligence system with BI features like data creation, automation, analysis, and visualisation. Clear Analytics also functions with Microsoft Power BI, cleaning and modelling various datasets with Power Query and Power Pivot.

12.Tableau: Needs No Introduction

Tableau is a powerful BI tool that specialises in data discovery and visualisation. The software allows to quickly analyse, visualise, and share data without IT intervention. Tableau works with various data sources, including Microsoft Excel, Oracle, MS SQL, Google Analytics, and SalesForce. Users will have access to well-designed, user-friendly dashboards. Tableau also provides several products, such as Tableau Desktop (for anyone) and Tableau Server (analytics for organisations), both of which can be run locally, as well as Tableau Online (hosted analytics for organisations) and others.

13.Oracle BI: Proactive Intelligence Power

Oracle BI is a business intelligence technology and application portfolio for enterprises. This technology provides nearly all business intelligence capabilities, including dashboards, proactive intelligence, ad hoc reporting, etc. Oracle is a reliable choice ideal for businesses that need to analyse large amounts of data from Oracle and non-Oracle sources. Data archiving, versioning, a self-service portal, and alerts/notifications are also essential features.

14.Domo: Predictive Analysis on the Go

Domo is a fully cloud-based business intelligence platform that integrates spreadsheets, databases, and social media data. The platform provides visibility and analysis at the micro and macro levels, including predictive analysis powered by Mr Roboto, their AI engine. From cash balances and lists of your best-selling products by region to marketing ROI calculations for each channel, Domo has got you covered.

15.IBM Cognos Analytics: Hidden Patterns in Data Discovered

Cognos Analytics is a business intelligence platform powered by AI that supports the entire analytics cycle. It helps to visualise, analyse, and share actionable insights, from data discovery to data operationalisation. The data is interpreted and presented in a visually appealing report, and AI allows the discovery of hidden patterns in the data.

The use of advanced business intelligence reporting tools makes tasks simple and manageable. Business intelligence platforms are subject to change based on business needs and the advancement of technologies. Still, they have proven to be a great way to accomplish strategic goals effectively and efficiently.