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Apple WWDC 2021, Facebook f8, Microsoft Build: What’s in it for Developers and Consumers this year

14 minutes read

Apple WWDC 2021 is the second all-virtual conference hosted by the company this year, one that will see both hardware announcements and software updates. WWDC 2021, which begins June 7 with the traditional Apple keynote will run the whole week long and will contain pavilions, daily recaps available to revisit, and more in this free-for-all developers virtual meet. 

WWDC 2021 is bringing big changes to iOS 15 and iPad OS 15, along with a new more powerful M2 chip and a redesigned MacBook Pro that gets rid of its maligned features like the Touch Bar, to re-introduce the HDMI port and MagSafe. 

Apple CEO Tim Cook began the keynote address welcoming “familiar” faces back again in the audience, virtual avatars aka Memoji instead of real people, given the ongoing pandemic. 

ALSO READ: Google I/O 2021: What’s in it for Developers and Consumers this Year

Here’s everything we noticed at the Apple WWDC 2021 keynote: 

iOS 15 

The new iOS update will come with a series of improvements including a better Facetime experience. FaceTime will now include features like Spatial Audio making calls more comfortable and natural, like you and the person on the other end are in the same room. The mic gets a Voice Isolation update, which, through the use of Machine Learning will block ambient noise and prioritize your voice. Another noticeable update is Wide Spectrum, to capture your voice and everything around you.  

The software update also introduces Portrait mode to blur backgrounds, and a grid view to enable multi-conversations with a highlighted tile to know who the speaker is. Users can also schedule individual FaceTime calls with Facetime links, similar to Zoom. Additionally, users can share their screen, music, TV show, or movie through a new feature called ShareTime, to enable a Watch Party of their own. FaceTime will, with this update, be supported on Android and Windows through a web browser.

iMessage, the messaging platform, available only on Apple devices, will now come with features that group similar images into galleries. A brand-new feature called “shared with you” will save links that people sent you and collects them in one place. It works across Safari, Apple Music, Apple TV, and Apple Podcasts.

ALSO READ: Here’s what a tech-enabled world will look like for future pandemic phases

Notifications will now have an updated design on the lock screen, featuring a clearer look. Titled the Focus feature, users can choose to go on Do Not Disturb mode or choose Work, Life hours to be able to receive notifications depending on their preferences, much like the OnePlus Zen Mode and Work-Life Balance feature that came with the OnePlus 7 series in 2019. 

Live Text, a new camera feature, will automatically identify and scan text or visuals in photographs. Another feature called Memories will use Machine Learning and AI to combine photos into galleries and add music from Apple Music. 

Apple Maps software is also updated with 3D data with this release. It now includes lanes, clearer city details, AR-led detailed directions, and more. The Weather app gets an interactive update where data and layout will change according to weather conditions. 

A new feature is also coming to AirPods called “conversation boost” which will help people better understand who they are talking to in real-time. Siri will be able to announce messages and read out your shopping list as well. Apple Wallet adds a new functionality which now includes corporate badges.

Quicknote is a fast and easy way to get to a note saved for later, while also allowing a user to jot notes using the Apple Pencil. Consumers can now add tags to organize their notes better and even mention others in shared notes.  

With iPadOS 15, Apple is adding features for multi-tasking, bringing widgets and app library to the iPad as well. Apple has also announced an iCloud+ subscription service with a focus on privacy. 

Privacy and Security: 

New privacy features, and a subscription-based iCloud+ was also announced at the keynote. Apple is now adding new privacy features across its devices. The Mail App, for instance, will have a feature called tracker-blockers to hide your IP address, location and other information that help building a digital personality for third-party apps. An App Tracker Report section in the Settings will allow users to see how often apps have used their info in the last seven days.

iCloud+ will also include a key feature called Private Relay, which essentially helps route web traffic through two separate servers, just like VPN.

Siri, on the other hand, has some new features including availability on third-party apps, and users can also request tasks from the Voice Assistant without an active internet connection. 

Speaking of legacy contacts, Apple has introduced a Digital Legacy Program that will help your trusted contacts to manage your account, close them et al, even when you’re no longer around. 

Digital Health: 

The latest Apple Watch software allows more interaction possibilities while also connecting health trackers that monitors everything from your gait to the sleep patterns via the Breathe app called Mindfulness and let’s you know as soon as it finds something out of the ordinary which can be addressed promptly. This is possible through Apple’s collaboration with a few electronic health record companies. If you’re away from your loved ones, the new software allows you to share health data too. 

New watch faces on Watch OS8 are available in Portrait mode and one also has the ability to write a text with their finger to send a text message. 

ALSO READ: What will ‘Behavioural Changes’ Mean for India’s Digital Health Future

Additionally, in the Workouts app, new workout types including TaiChi and Pilates have been added guided by popular names such as Jeanette Jenkins as well as a new Artist Spotlight series that offers workouts on the music of Lady Gaga, Keith Urban, and more.

macOS Monterey: 

At the WWDC 2021 keynote address last night, Apple announced a new version of macOS. Titled Monterey, after the pristine beach town in California’s central coast, the new macOS brings a number of features including multiple screen-usage while using the same mouse and keyboard across a Mac or an iPad. This feature is called Universal Control. 

iOS devices can (for the first time) beam their screen to a Mac, thanks to AirPlay. The Safari web browser has also got a redesign with new and improved features including tab grouping and tab bookmarking. 

What piqued your interest the most at this year’s Apple WWDC? Facebook f8, held earlier this month also had a few interesting announcements. Take a look. 

WIIFM at Facebook f8? 

Facebook f8, held on June 2 this year kicked off with a promise that Facebook was returning to its roots and focusing on the developer community for this year’s virtual event. 

“This year we are refocusing F8 on developers,” Mark Zuckerberg said. “Some of the most important services in the world started when someone looked at an existing issue, and just found a better way to build. And I’m optimistic that some of the next generation of services are going to start right here with you.”  

On the business messaging front, Facebook announced that its Messenger API for Instagram is available to all developers. The social media giant is also testing a way for people to opt into messaging with businesses through a new feature called Login Connect with Messenger. 

Through WhatsApp Business API, it’s now easier for businesses to get started with using the tool effectively for their businesses. Among its key updates, Facebook said it has reduced the entire API onboarding process from weeks to five minutes. The company also announced new WhatsApp messaging features with an aim to give people a quicker way to make a selection when interacting with a business’s chatbot on WhatsApp. 

Augmented Reality, AI and Machine Learning: 

Facebook’s development of its futuristic augmented reality glasses is still ongoing, but the company has exhibited broad ambitions in terms of its AR experiences built on its SparkAR software. In the near future, Facebook has said that it wants to make it easier for developers to build augmented reality effects for group calls via its new Multipeer API.  

The SparkAR platform now has 600,000 creators in 190 countries, with 2 million AR filters and effects created to date, according to Facebook. 

PyTorch, the deep learning framework co-developed by Facebook in 2016, is now becoming the default framework for building all its AI and machine learning models in the foreseeable future. 

“PyTorch not only makes our research and engineering work more effective, collaborative, and efficient, it also allows us to share our work as open-source PyTorch libraries and learn from the advances made by the thousands of PyTorch developers all over the world,” Facebook said in a blog post. 

Missed Microsoft Build? Here are key highlights tailor-made for you: 

Microsoft Build, also a developer conference, was also held virtually this year from May 25 to 27. 

Following his keynote address, Microsoft CEO Satya Nadella wrote on a LinkedIn post, “As computing becomes embedded in every aspect of our lives, there will be no longer such thing as the tech sector. The world will be transformed through tech intensity at scale. Every organization will need to not only adopt the latest technology, but more importantly, build their own unique digital technology, or be left behind.”

“We are building the platform for platform creators. It’s not about setting new rules or constraints that dictate how or what you should build. It’s not even about celebrating our own innovation. It’s about enabling your innovation and creating new opportunities for you,” he continued. 

From Microsoft Teams that allows users to complete projects from any location and at any time without needing to switch across different apps and data, to Windows Updates providing GUI support on Windows Subsystem for Linux (WSL), it will also allow seamless integrations with other workflows with Linux, GUI apps, and GPU-accelerated ML training.

In terms of privacy and security, Microsoft announced the integration of its Azure Security Center with GitHub. This integration will further enhance collaboration between the development and security teams. Interestingly, this collaborative effort will feature an update to enable security teams to be aware of the holistic development life-cycle instead of trying and fixing bugs only once the software is released. This measure will further allow the DevSecOps teams to run vulnerability scans, resolve findings, and visualize the security of workflows within their CI/CD pipeline.

The company also announced key updates to its Azure AI services, including Azure Bot Services, Azure Video Analyzer, and more. That’s not all, Microsoft also announced ML capabilities updates to accelerate its AI model deployment, namely Azure Machine Learning Managed Endpoints and Power Fx.

Automatic Aggregations was yet another feature that debuted at MS Build this year. Power BI dataflows that suitably handle streaming data sources, starting with Azure Event Hubs and Azure IoT Hubs, promises to make streaming data and real-time analytics accessible. 

Microsoft also introduced a low-code programming tool that allows users to write code without any prior coding knowledge. Called Power App Ideas, is the first-of-its-kind collaborative effort between Microsoft and artificial intelligence (AI) research company OpenAI. The app uses OpenAI’s Generative Pre-Trained Transformer-3 (GPT-3) AI model, among one of the highly advanced natural language AI models in the world today. 

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Lake, Lakehouse, or Warehouse? Picking the Perfect Data Playground

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In 1997, the world watched in awe as IBM’s Deep Blue, a machine designed to play chess, defeated world champion Garry Kasparov. This moment wasn’t just a milestone for technology; it was a profound demonstration of data’s potential. Deep Blue analyzed millions of structured moves to anticipate outcomes. But imagine if it had access to unstructured data—Kasparov’s interviews, emotions, and instinctive reactions. Would the game have unfolded differently?

This historic clash mirrors today’s challenge in data architectures: leveraging structured, unstructured, and hybrid data systems to stay ahead. Let’s explore the nuances between Data Warehouses, Data Lakes, and Data Lakehouses—and uncover how they empower organizations to make game-changing decisions.

Deep Blue’s triumph was rooted in its ability to process structured data—moves on the chessboard, sequences of play, and pre-defined rules. Similarly, in the business world, structured data forms the backbone of decision-making. Customer transaction histories, financial ledgers, and inventory records are the “chess moves” of enterprises, neatly organized into rows and columns, ready for analysis. But as businesses grew, so did their need for a system that could not only store this structured data but also transform it into actionable insights efficiently. This need birthed the data warehouse.

Why was Data Warehouse the Best Move on the Board?

Data warehouses act as the strategic command centers for enterprises. By employing a schema-on-write approach, they ensure data is cleaned, validated, and formatted before storage. This guarantees high accuracy and consistency, making them indispensable for industries like finance and healthcare. For instance, global banks rely on data warehouses to calculate real-time risk assessments or detect fraud—a necessity when billions of transactions are processed daily, tools like Amazon Redshift, Snowflake Data Warehouse, and Azure Data Warehouse are vital. Similarly, hospitals use them to streamline patient care by integrating records, billing, and treatment plans into unified dashboards.

The impact is evident: according to a report by Global Market Insights, the global data warehouse market is projected to reach $30.4 billion by 2025, driven by the growing demand for business intelligence and real-time analytics. Yet, much like Deep Blue’s limitations in analyzing Kasparov’s emotional state, data warehouses face challenges when encountering data that doesn’t fit neatly into predefined schemas.

The question remains—what happens when businesses need to explore data outside these structured confines? The next evolution takes us to the flexible and expansive realm of data lakes, designed to embrace unstructured chaos.

The True Depth of Data Lakes 

While structured data lays the foundation for traditional analytics, the modern business environment is far more complex, organizations today recognize the untapped potential in unstructured and semi-structured data. Social media conversations, customer reviews, IoT sensor feeds, audio recordings, and video content—these are the modern equivalents of Kasparov’s instinctive reactions and emotional expressions. They hold valuable insights but exist in forms that defy the rigid schemas of data warehouses.

Data lake is the system designed to embrace this chaos. Unlike warehouses, which demand structure upfront, data lakes operate on a schema-on-read approach, storing raw data in its native format until it’s needed for analysis. This flexibility makes data lakes ideal for capturing unstructured and semi-structured information. For example, Netflix uses data lakes to ingest billions of daily streaming logs, combining semi-structured metadata with unstructured viewing behaviors to deliver hyper-personalized recommendations. Similarly, Tesla stores vast amounts of raw sensor data from its autonomous vehicles in data lakes to train machine learning models.

However, this openness comes with challenges. Without proper governance, data lakes risk devolving into “data swamps,” where valuable insights are buried under poorly cataloged, duplicated, or irrelevant information. Forrester analysts estimate that 60%-73% of enterprise data goes unused for analytics, highlighting the governance gap in traditional lake implementations.

Is the Data Lakehouse the Best of Both Worlds?

This gap gave rise to the data lakehouse, a hybrid approach that marries the flexibility of data lakes with the structure and governance of warehouses. The lakehouse supports both structured and unstructured data, enabling real-time querying for business intelligence (BI) while also accommodating AI/ML workloads. Tools like Databricks Lakehouse and Snowflake Lakehouse integrate features like ACID transactions and unified metadata layers, ensuring data remains clean, compliant, and accessible.

Retailers, for instance, use lakehouses to analyze customer behavior in real time while simultaneously training AI models for predictive recommendations. Streaming services like Disney+ integrate structured subscriber data with unstructured viewing habits, enhancing personalization and engagement. In manufacturing, lakehouses process vast IoT sensor data alongside operational records, predicting maintenance needs and reducing downtime. According to a report by Databricks, organizations implementing lakehouse architectures have achieved up to 40% cost reductions and accelerated insights, proving their value as a future-ready data solution.

As businesses navigate this evolving data ecosystem, the choice between these architectures depends on their unique needs. Below is a comparison table highlighting the key attributes of data warehouses, data lakes, and data lakehouses:

FeatureData WarehouseData LakeData Lakehouse
Data TypeStructuredStructured, Semi-Structured, UnstructuredBoth
Schema ApproachSchema-on-WriteSchema-on-ReadBoth
Query PerformanceOptimized for BISlower; requires specialized toolsHigh performance for both BI and AI
AccessibilityEasy for analysts with SQL toolsRequires technical expertiseAccessible to both analysts and data scientists
Cost EfficiencyHighLowModerate
ScalabilityLimitedHighHigh
GovernanceStrongWeakStrong
Use CasesBI, ComplianceAI/ML, Data ExplorationReal-Time Analytics, Unified Workloads
Best Fit ForFinance, HealthcareMedia, IoT, ResearchRetail, E-commerce, Multi-Industry
Conclusion

The interplay between data warehouses, data lakes, and data lakehouses is a tale of adaptation and convergence. Just as IBM’s Deep Blue showcased the power of structured data but left questions about unstructured insights, businesses today must decide how to harness the vast potential of their data. From tools like Azure Data Lake, Amazon Redshift, and Snowflake Data Warehouse to advanced platforms like Databricks Lakehouse, the possibilities are limitless.

Ultimately, the path forward depends on an organization’s specific goals—whether optimizing BI, exploring AI/ML, or achieving unified analytics. The synergy of data engineering, data analytics, and database activity monitoring ensures that insights are not just generated but are actionable. To accelerate AI transformation journeys for evolving organizations, leveraging cutting-edge platforms like Snowflake combined with deep expertise is crucial.

At Mantra Labs, we specialize in crafting tailored data science and engineering solutions that empower businesses to achieve their analytics goals. Our experience with platforms like Snowflake and our deep domain expertise makes us the ideal partner for driving data-driven innovation and unlocking the next wave of growth for your enterprise.

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