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Here is Everything Apple Announced at WWDC 2016

Apple’s WWDC this year was full of incremental updates to OS’s for the Mac, iPhone, Watch, and TV, as well as moves to open up services like Siri and iMessage to developers. A lot of the changes were geared toward moving between Apple devices easier — Siri is now on desktop, and Apple Pay will now work on Safari, for example. There were also a bunch of redesigns: new notifications and lock screen interactions for iOS; a new command center for the (faster) Apple Watch; and changes to Apple News, Music, Maps, and other services.
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We’re updating all day, so come back for additional news later.

MacOS has a new name, more continuity across devices, and Siri

OS X is now macOS, and this iteration will be called Sierra. The public beta will launch in July with the final version coming in the fall. One of the big focuses of the new OS is continuity across devices. Craig Federighi demonstrated a feature called Universal Clipboard, which allows users to copy and paste across multiple Apple devices. You can also save your Mac desktop to the cloud and access it from a different computer using iCloud drive. There are other smaller updates as well, including a storage-saving measure that moves old files to the cloud and a way to unlock your Mac using your Apple Watch.
Sierra will also bring Siri to the desktop. Siri will be accessible in the dock as well as in the top-right corner near Spotlight. You’ll be able to use voice commands to find files, search the web, send messages, and other standard Siri functions.3060889-slide-p-1-ossierra

Apple pay is coming to the web

You’ll be able to use Apple Pay to make payments online through Safari. Authentication will work through TouchID, either through your phone or Apple Watch, eliminating the need to type credit card details. Apple Pay is available in the US, UK, Canada, Australia, and Singapore, and will be rolling out to Switzerland, France, and Hong Kong.apple-pay-930x488

The apple watch gets faster and ADDS new features

watchOS 3 brings a host of updates, but perhaps most importantly, it loads apps seven times faster than the previous OS, thanks to background refreshing and keeping apps stored in memory. Navigation supposedly will be easier on the new OS, too. The side button can be used to access a “dock,” which allows wearers to scroll through their apps, and the Watch will act a little more like an iPhone with a new Control Center. A swipe up on the Watch allows wearers to quickly switch into airplane mode or Do Not Disturb, just like the iPhone.
Other new features include a keyboard called “Scribble” that wearers can use to respond to a message. Instead of typing or dictating a response, they can draw out each individual letter. It works in either English or Chinese. Apple Watches will also come with a new SOS feature, which activates when the side button is held down and calls 911 and sends location information to first responder and emergency contacts. It’ll also share users’ medical ID, which displays their allergies, age, and existing medical conditions. The feature works internationally and will call country-specific emergency numbers, so long as the watch is tethered to a phone or is connected to Wi-Fi.

Apple emphasized fitness with the introduction of new activity-specific watch faces, a meditation app called “Breathe,” and activity sharing to view friends’ fitness levels.apple-watch-2concept-by-eric-huismann

ios gets a slew of updates

Craig Federighi called the iOS changes “the biggest iOS release ever for our users,” including complete redesigns for Music and Maps, new notifications, and an expanded role for 3D Touch. A new feature called “raise and wake” will wake the lock screen when you lift your phone, revealing redesigned notifications that you can interact with using 3D touch.

Apple news gets a redesign and supports subscriptions

Apple News now features over 2,000 publications and over 60 million monthly readers. Apple is rolling out an all-new design that features clear sections, including Top News, Trending, and Sports. The app pulls together new sections based on your reading habits, and includes a Featured Stories section with editor picks. Apple News now also features subscriptions, which means you can subscribe and read full newspapers and magazines from the app. It will also send breaking news notifications and deliver them to your lock screen.

Apple music gets a discover playlist and a complete redesign

After only a year of existence, Apple Music is getting a complete redesign. New sections make it easier to navigate, including one section for downloaded music and another for recently added songs and albums. Apple also appears to be coming directly for Spotify with its new “discovery mix” that tailors a playlist to listeners’ tastes. There will also be daily curated playlists and new sections to help users find new music curated by Apple’s music editors. You can also read song lyrics now.

Maps is redesigned with navigation in mind

Maps is getting a whole new feel. Its redesign will show more of a map when a user opens the app. Users can also book rides through Maps, pay for them with Apple Pay, and make restaurant reservations. Navigation is getting easier too, with directions that include traffic. Maps is also coming to CarPlay, which will show traffic and offer alternative routes, as well as precise navigation right from a car’s display.

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Messages Get snazzier

Apple is revamping iMessage to include bigger emoji as well as suggestions for turning certain keywords into emoji. People can share songs directly from Apple Music and write notes to one another in their own handwriting. There are animated effects — like strobe lights, balloons, and confetti — and invisible ink hides messages until they’re swiped over. Invisible ink! Developers are also getting access to Messages and can develop apps like stickers. iMessage is turning into some kind of Snapchat-WhatsApp-Facebook Messenger conglomerate.

Photos takes on google photos

Photos is being updated with new features to help you organize and manage your collection. You can organize your collection automatically by person using facial recognition. The app is also adding Memories, which bundles together photos according to events and locations. You can also create a montage set to music automatically from Memories, much as you’re able to do in Google Photos.

Voicemail transcription comes to ios 10

iOS 10 will now feature voicemail transcription, which will automatically transcribe voicemails and offer them up like texts. In addition, iOS is taking on spam calls: the iOS will support APIs that can alert you to possible spam calls and warn you before you pick up. With VoIP, you’ll be able to see caller ID right on the lock screen.iorpxzsi1awm6lsqhnug1

tvos is all grown-up

tvOS is less than a year old but now hosts 1,300 video channels and over 6,000 apps. That library is going to be expanding shortly: Dish’s Sling is coming to tvOS today; Fox Sports Go is coming later this summer; and Molotov, a French TV service, is coming next month. Apple is rolling out a new Apple TV remote app, which will have all the functionality of the… Apple TV remote. You’ll be able to use touch for navigation, Siri for voice command, and the phone’s built-in sensors for gaming control. Plus, you’ll have your trusty keyboard. Siri will now be able to search through the service’s 650,000 movies and shows, as well as live channels by name or category (“German high school comedy from 1962, please”). You’ll also now be able to use Siri to search in YouTube.
Apple’s also introducing a single sign-on system that lets your log into all of the network apps at once. You’ll have a page that shows you all the channels you have access to. Download a channel app onto your phone, and it’ll automatically appear on your tvOS. Seamless integration, folks.
And Apple quickly introduced two kits for developers: ReplayKit, which lets you live broadcast gameplay or save it for later, and HomeKit, which will let you control all the devices in your house, including tvOS. tvOS will roll out in a free upgrade this fall.

Siri is opening up to app developers

Siri, which now services over 2 billion requests per day, is now opening up to developers. That means you’ll be able to ask Siri to send a message through WeChat, ask it to call an Uber, search for photos on Pinterest and start and stop your workout apps all with voice command.

Predictive type takeover

QuickType will bring Siri intelligence to the keyboard, using deep learning to enable more intelligent predictive typing using expanded context. That means Message can now help you with text responses, and offer up your location when someone is wondering where you are. Now that it’s open to developers you’ll be able to look up movies or restaurants straight from the keyboard. The QuickType keyboard will also now support multilingual typing. Apple also made a point of noting that, unlike Google, its AI analysis will stay on your device and won’t transmit your texts to the cloud.

What’s next

WWDC was packed with updates, many of which seem minor on their own, but taken together could make it easier navigate Apple’s ecosystem. With the Watch, incremental changes in speed and the command center could go a long way toward making it a more appealing device, and the new HomeKit hub could make connected appliances more attractive. It remains to be seen how well all these services work outside the Apple ecosystem, and whether opening up things like Apple Pay and Siri will be enough to surmount the lead of companies like Amazon, which has been aggressive about forming partnerships and developing frictionless ways to purchase. And of course, we’ll still be waiting for the Apple car.

If any queries approach us on hello@mantralabsglobal.com

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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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