The first day of the Google I/O 2018 consisted over 5,000 developers, designers, and managers gathered at Shoreline, Amphitheatre to witness the opening day with a keynote by Google CEO Sundar Pichai.

Let’s dive into the key announcements that were made!

Google I/O: Android P

Google launched Android P, the latest version of the operating system that runs on Android devices. The Android P beta is available for certain devices such as the Essential Phone, Google Pixel 2, Nokia 7 plus, Sony Xperia XZ2, Vivo and Xiaomi Mi Mix 2S. Users of these devices can update to Android P beta immediately. There are a bunch of features that Google added to Android P.

Shush: This feature ensures that there are no notifications coming in from your apps when your phone is turned face down.
App Dashboard: This is a dashboard that shows how much time you spend on your apps each day. This allows you to know which apps you spend so much time on.
App Timer: With the app timer, you’d get a notification when you spend more than the allocated time specified for engaging with an app.
Slices and Actions: A slice is a piece of app content and action that can be surfaced outside of the app without opening the app itself. They are UI templates that can display rich and interactive content from your app within the Google Search app.

Google I/O: AI in Google

Google AI

Google has worked hard over the last few years on improving every aspect of their products with AI and Machine Learning. This year they made some key announcements about new products and also the existing products that are improved with AI. Google announced that its research division has been rebranded to Google AI. This rebranding came as a result of Google’s continued focus on Computer vision, Natural language processing, and neural networks.

Google Assistant

The Google Assistant has been greatly improved. It will be available in 6 new voices including the voice of popular musician, John Legend. Furthermore, Google announced a new technology called Duplex, it is an AI system for natural conversations that’ll enable your Google Assistant to make conversations on your behalf like a lunch reservation at a restaurant, and setting up a meeting.

Until now every time we need the Google Assistant to do something, we usually start every conversation with Hey, Google! Now, we don’t have to do that anymore because the Google Assistant now has support for continued conversations. Google Assistant also has a new feature called Pretty Please. This feature was added to help train kids to avoid being commanding when asking for favors. With the new Pretty Please feature, kids can be taught to always make polite requests.

Google Lens

The Google Lens is also updated with some amazing new features. Now, Google Lens allows you copy-paste text from a photo in the real world to your phone. It also provides the ability to take a photo and instantly provide information about the objects and landmarks in the photo. Google Lens introduced Style Match. With Style Match, you could take a photo of a fashion item such as a shirt, blouse, shoe, or a fancy lamp. Once captured, a blue dot appears on the photo. Tap the dot, and Google Lens will provide lists of items similar to it. What a time to be alive!

Google Maps

Google announced better navigation for Google Maps aided by AI. The Google Maps was difficult for users that are not familiar with the North, South, West, East form of directions. The new Google Maps provides a street view with a very obvious direction sign. With Google Assistant in navigation in Google Maps, it provides users a better description of routes. It also adds a navigation animal that allows the map user quickly identify the route to take.

Google News

Google is keen on getting users a seamless way of catching up with news all over the world. Google is rolling out a new AI improved version of the Google News product that provides an great way to catch up with events around the world. This improved product replaces Google Play Newsstand and Google News app. It will be available on Android, iOS and the web in 127 countries by next week.

Stay tuned for more updated from Google I/O 2018!!

Silent Drains: How Poor Data Observability Costs Enterprises Millions

By : Sampada S M

Published on Jan 30, 2025

Updated on Feb 4, 2025

Data Observability Data Pipeline

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data health dashboard, the retailer was able to prevent costly downtime and ensure seamless data operations. The result? Enhanced data lineage tracking and reduced operational overhead.

2. Fixing Silent Pipeline Failures

Monte Carlo’s data observability solutions have saved organizations from silent data pipeline failures. For example, a Salesforce password expiry caused updates to stop in the salesforce_accounts_created table. Monte Carlo flagged the issue, allowing the team to resolve it before it caught the executive attention. Similarly, an authorization issue with Google Ads integrations was detected and fixed, avoiding significant data loss.

3. Forbes Optimizes Performance

To ensure its website performs optimally, Forbes turned to Datadog for data observability. Previously, siloed data and limited access slowed down troubleshooting. With Datadog, Forbes unified observability across teams, reducing homepage load times by 37% and maintaining operational efficiency during high-traffic events like Black Friday.

4. Lenovo Maintains Uptime

Lenovo leveraged observability, provided by Splunk, to monitor its infrastructure during critical periods. Despite a 300% increase in web traffic on Black Friday, Lenovo maintained 100% uptime and reduced mean time to resolution (MTTR) by 83%, ensuring a flawless user experience.

Why Every Enterprise Needs Data Observability Today

1. Prevent Costly Downtime

Data downtime can cost enterprises up to $9,000 per minute. Imagine a retail giant facing data pipeline failures during peak sales—inventory mismatches lead to missed opportunities and unhappy customers. Data observability proactively detects anomalies, like sudden drops in data volume, preventing disruptions before they escalate.

2. Boost Confidence in Data

Poor data quality costs the U.S. economy $3.1 trillion annually. For enterprises, accurate, observable data ensures reliable decision-making and better AI outcomes. For instance, an insurance company can avoid processing errors by identifying schema changes or inconsistencies in real-time.

3. Enhance Collaboration

When data pipelines fail, teams often waste hours diagnosing issues. Data observability simplifies this by providing clear insights into pipeline health, enabling seamless collaboration across data engineering, data analytics, and data operations teams. This reduces finger-pointing and accelerates problem-solving.

4. Stay Agile Amid Complexity

As enterprises scale, data sources multiply, making Data pipeline monitoring and data pipeline management more complex. Data observability acts as a compass, pinpointing where and why issues occur, allowing organizations to adapt quickly without compromising operational efficiency.

The Bigger Picture:

Are you relying on broken roads in your data metropolis, or are you ready to embrace a system that keeps your operations smooth and your outcomes predictable?

Just as humanity evolved from carving records on clay tablets to storing data in the cloud, the way we manage and interpret data must evolve too. Data observability is not just a tool for keeping your data clean; it’s a strategic necessity to future-proof your business in a world where insights are the cornerstone of success.

At Mantra Labs, we understand this deeply. With our partnership with Rakuten, we empower enterprises with advanced data observability solutions tailored to their unique challenges. Let us help you turn your data into an invaluable asset that ensures smooth operations and drives impactful outcomes.

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