1-888-317-7920 info@2ndwatch.com

Migrating Data to Snowflake – An Overview

When considering migrating your data to the cloud, everyone’s familiar with the three major cloud providers – AWS, Google Cloud, and Microsoft Azure. But there are a few other players you should also take note of. Snowflake is a leading cloud data platform that offers exceptional design, scalability, simplicity, and return on investment (ROI).

What is Snowflake?

The Snowflake cloud data platform was born in the cloud for data warehousing. It’s built entirely to maximize cloud usage and designed for almost unlimited scalability. Users like the simplicity, and businesses gain significant ROI from the wide range of use cases Snowflake supports.

Out of the box, Snowflake is easy to interact with through its web interface. Without having to download any applications, users can connect with Snowflake and create additional user accounts for a fast and streamlined process. Additionally, Snowflake performs as a data platform, rather than just a data warehouse. Data ingestion is cloud native and existing tools enable effortless data migration.

Business Drivers

The decision to migrate data to a new cloud environment, or data warehousing solution, needs to be based on clearly defined value. Why are you making the transition? What’s your motivation? Maybe you need to scale up, or there’s some sort of division or business requirement for migration. Often times, companies have a particular implementation that needs to change, or they have specific needs that aren’t being met by their current data environment.

Take one of our clients, for instance. When the client’s company was acquired, they came to utilize a data warehouse shared by all the companies the acquiring company owned. When the client was eventually sold, they needed their own implementation and strategy for migrating data into the cloud. Together, we took the opportunity to evaluate some of the newer data platform tools, like Snowflake, for their specific business case and to migrate quickly to an independent data platform.

With Snowflake, set up was minimal and supported our client’s need for a large number of database users. Migrating from the shared data warehouse to Snowflake was relatively easy, and it gave all users access through a simple web interface. Snowflake also provided more support for unstructured data usage, which simplified querying things like JSON or nested data.

Implementation

Migrating data to Snowflake is generally a smooth transition because Snowflake accepts data from your existing platform. For instance, if data is stored in Amazon S3, Google Cloud, or Azure, you can create Snowflake environments in each then ingest the data using SQL commands and configuration. Not only can you run all the same queries with minor tweaks and get the same output, but Snowflake also fits additional needs and requirements. If you’ve worked in SQL in any manner – on an application database, or in data warehousing – training is minimal.

Another advantage with Snowflake is its ability to scale either horizontally or vertically to pull in any amount of data. And since it is cloud native, Snowflake has embraced the movement toward ‘pay as you go’ – in fact, that’s their entire structure. You only pay for the ingestion time and when the data warehouse is running. After that, it shuts off, and so does your payment. Cost-effective implementation lets you experiment, compare, test, and iterate on the best way to migrate each piece of your data lifecycle.

Long Term Results

Snowflake has yielded successful data migrations with users because of its ease of use and absence of complications. Users also see performance improvements because they’re able to get their data faster than ever and they can grow with Snowflake, bringing in new and additional data sources and tools, taking advantage of artificial intelligence and machine learning, increasing automation, and experimenting and iterating.

From a security and governance perspective, Snowflake is strong. Snowflake enforces a multi-layer security structure, including user management. You can grant access to certain groups, organize them accordingly, integrate with your active directory, and have it run with those permissions. You assign an administrator to regulate specific accessibility for tables in specified areas. Snowflake also lets you choose your desired security level during implementation. You have the option of enterprise level, HIPAA compliance, and a maximum security level with a higher rate per second.

Do you want to explore data migration opportunities? Make the most of your data by partnering with trusted experts. We’re here to help you migrate, store, and utilize data to grow your business and streamline operations. If you’re ready to the next step in your data journey, Contact Us.

Learn more about 2nd Watch Data and Analytics services

-Sam Tawfik, Sr Product Marketing Manager, Data & Analytics

Facebooktwitterlinkedinmailrss

Cloud Governance: Why It Is Critical to the Success of Cloud Adoption

According to a 2019 report by Unisys, 37% of all cloud adoption initiatives fail to realize their objectives.

The report, although disturbing, is not shocking by any measure. Although businesses continue to migrate to the cloud, many have failed to make it a core part of their business strategy. The reasons for this vary – poorly trained staff, inability to utilize cloud resources effectively, or the absence of a strategy that leverages the power of cloud.

For these reasons and many others, businesses incur unexpected costs, unproductive workflows, and cybersecurity risks to their data on the cloud. These organizations need a set of protocols for utilizing cloud resources efficiently, effectively, and securely. In short, they need a cloud governance framework that enables them to extract the benefits of the cloud.

Organizations can fully realize these benefits only when their cloud policies are designed to leverage them. Therefore, a well-designed cloud governance framework is critical to the success of cloud adoption. What is cloud governance and how does it lay the foundation for the success of your cloud adoption?

Download our white paper to learn about the role of cloud governance in successful cloud adoption.

-Mir Ali, Field CTO

Facebooktwitterlinkedinmailrss

Cloud Crunch Podcast: Multi-Cloud – Is it Really Worth It?

The promise of multi-cloud suggests enterprises should be able to run their applications and workloads in whichever cloud environment makes the most sense from a cost, performance or functionality perspective. But the reality of the situation can be very different in practice, as enterprises grapple with how best to make technologies created by competing suppliers play nicely together. Contributor and Analyst to Forbes, CBS interactive, Information Today, Inc., and RTInsights, Joseph McKendrick, joins today’s episode to give his perspective on the value of a multi-cloud strategy. Listen now on Spotify, iTunes, iHeart Radio, Stitcher, or wherever you get your podcasts.

We’d love to hear from you! Email us at CloudCrunch@2ndwatch.com with comments, questions and ideas.

Facebooktwitterlinkedinmailrss

Cloud Crunch Podcast: 2020 Enterprise Cloud Trends

How are enterprises responding to the COVID 19 pandemic and how is it affecting their cloud usage? We take a look at 6 key findings from 2nd Watch’s “Enterprise Cloud Trends” survey and discuss what the survey indicates and what we‘re seeing from our own clients. Listen now on Spotify, iTunes, iHeart Radio, Stitcher, or wherever you get your podcasts.

We’d love to hear from you! Email us at CloudCrunch@2ndwatch.com with comments, questions and ideas.

Facebooktwitterlinkedinmailrss

3 Ways McDonald’s France is Preparing their Data for the Future

Data access is one of the biggest influences on business intelligence, innovation, and strategy to come out of digital modernization. Now that so much data is available, the competitive edge for any business is derived from understanding and applying it meaningfully. McDonald’s France is gaining business-changing insights after migrating to a data lake, but it’s not just fast food that can benefit. Regardless of your industry, gaining visibility into and governance around your data is the first step for what’s next.

1. No More Manual Legacy Tools

Businesses continuing to rely on spreadsheets and legacy tools that require manual processes are putting in a lot more than they’re getting out. Not only are these outdated methods long, tedious, subject to human error, and expensive in both time and resources – but there’s a high probability the information is incomplete or inaccurate. Data-based decision making is powerful, however, without a data platform, a strong strategy, automation, and governance, you can’t easily or confidently implement takeaways.

Business analysts at McDonald’s France historically relied on Excel-based modeling to understand their data. Since partnering with 2nd Watch, they’ve been able to take advantage of big data analytics by leveraging a data lake and data platform. Architected from data strategy and ingestion, to management and pipeline integration, the platform provides business intelligence, data science, and self-service analytics. Now, McDonald’s France can rely on their data with certainty.

2. Granular Insights Become Opportunities for Smart Optimization

Once intuitive solutions for understanding your data are implemented, you gain finite visibility into your business. Since completing the transition from data warehouse to data lake, McDonald’s France has new means to integrate and analyze data at the transaction level. Aggregate information from locations worldwide provides McDonald’s with actionable takeaways.

For instance, after establishing the McDonald’s France data lake, one of the organization’s initial projects focused on speed of service and order fulfilment. Speed of service encompasses both food preparation time and time spent talking to customers in restaurants, drive-thrus, and on the online application. Order fulfilment is the time it takes to serve a customer – from when the order is placed to when it’s delivered. With transaction-level purchase data available, business analysts can deliver specific insights into each contributing factor of both processes. Maybe prep time is taking too long because restaurants need updated equipment, or the online app is confusing and user experience needs improvement. Perhaps the menu isn’t displayed intuitively and it’s adding unnecessary time to speed of service.

Multiple optimization points provide more opportunity to test improvements, scale successes, apply widespread change, fail fast, and move ahead quickly and cost-effectively. Organizations that make use of data modernization can evolve with agility to changing customer behaviors, preferences, and trends. Understanding these elements empowers businesses to deliver a positive overall experience throughout their customer journey – thereby impacting brand loyalty and overall profit potential.

3. Machine Learning, Artificial Intelligence, and Data Science

Clean data is absolutely essential for utilizing machine learning (ML), artificial intelligence (AI), and data science to conserve resources, lower costs, enable customers and users, and increase profits. Leveraging data for computers to make human-like decisions is no longer a thing of the future, but of the present. In fact, 78% of companies have already deployed ML, and 90% of them have made more money as a result.

McDonald’s France identifies opportunity as the most important outcome of migrating to a data lake and strategizing on a data platform. Now that a wealth of data is not only accessible, but organized and informative, McDonald’s looks forward to ML implementation in the foreseeable future. Unobstructed data visibility allows organizations in any industry to predict the next best product, execute on new best practices ahead of the competition, tailor customer experience, speed up services and returns, and on, and on. We may not know the boundaries of AI, but the possibilities are growing exponentially.

Now it’s Time to Start Preparing Your Data

Organizations worldwide are revolutionizing their customer experience based on data they already collect. Now is the time to look at your data and use it to reach new goals. 2nd Watch Data and Analytics Services uses a five-step process to build a modern data management platform with strategy to ingest all your business data and manage the data in the best fit database. Contact Us to take the next step in preparing your data for the future.

-Ian Willoughby, Chief Architect and Vice President

Listen to the McDonald’s team talk about this project on the 2nd Watch Cloud Crunch podcast.

Facebooktwitterlinkedinmailrss

McDonald’s France Gains Business-Changing Insights from New Data Lake

McDonald’s is famous for cheeseburgers and fries, but with 1.5 million customers a day, and each transaction producing 20 to 30 data points, it has also become a technology organization. With the overarching goal to improve customer experience, and as a byproduct increase conversion and brand loyalty, McDonald’s France partnered with 2nd Watch to build a data lake on AWS.

Customer Priorities Require Industry Shifts

As is common in many industries today, the fast-food industry has shifted from a transaction centric view to a customer centric view. The emphasis is no longer on customer satisfaction, but on customer experience. It’s this variable that impacts conversion rate and instills loyalty. Consequently, McDonald’s wanted to build a complete perspective of a customer’s lifetime value, with visibility into each step of their journey. Understanding likes and dislikes based on data would give McDonald’s the opportunity to improve experience at a variety of intersections across global locations.

McDonald’s is a behemoth in its size, multi-national reach, and the abundance of data it collects. Making sense of that data required a new way of storing and manipulating it, with flexibility and scalability. The technology necessary to accomplish McDonald’s data goals has significantly reduced in cost, while increasing in efficiency – key catalysts for initiating the project within McDonald’s groups, gaining buy-in from key stakeholders, and engaging quickly.

From Datacenter to Data Lake

To meet its data collection and analysis needs, McDonald’s France needed a fault-tolerant data platform equipped with data processing architecture and a loosely coupled distribution system. But, the McDonald’s team needed to focus on data insights rather than data infrastructure, so they partnered with 2nd Watch to move from a traditional data warehouse to a data lake, allowing them to reduce the effort required to analyze or process data sets for different properties and applications.

During the process, McDonald’s emphasized the importance of ongoing data collection from anywhere and everywhere across their many data sources. From revenue numbers and operational statistics to social media streams, kitchen management systems, commercial, regional, and structural data – they wanted everything stored for potential future use. Historical data will help to establish benchmarks, forecast sales projections, and understand customer behavior over time.

The Data Challenges We Expect…And More

With so much data available, and the goal of improving customer experience as motivation, McDonald’s France wanted to prioritize three types of data – sales, speed of service, and customer experience. Targeting specific sets of data helps to reduce the data inconsistencies every organization faces in a data project. While collecting, aggregating, and cleaning data is a huge feat on its own, McDonald’s France also had to navigate a high level of complexity.

As an omnichannel restaurant, McDonald’s juggles information from point of sales systems with sales happening online, offline, and across dozens of different locations. Data sources include multiple data vendors, mobile apps, loyalty programs, customer relationship management (CRM) tools, and other digital interfaces. Combined in one digital ecosystem, this data is the force that drives the entire customer journey. Once it’s all there, the challenge is to find the link for any given customer that transforms the puzzle into a holistic picture.

Endless Opportunities for the Future

McDonald’s France now has visibility into speed of service with a dedicated dashboard and can analyze and provide syntheses of that data. National teams can make data-based, accurate decisions using the dashboard and implement logistical changes in operations. They’re able to impact operational efficiency using knowledge around prep time to influence fulfilment.

The data lake was successful in showing the organization where it was losing opportunities by not taking advantage of the data it had. McDonald’s also proved it was possible, affordable, and advantageous to invest in data. While their data journey has only begun, these initial steps opened the door to new data usage possibilities. The models established by McDonald’s France will be used as an example to expand data investments throughout the McDonald’s corporation.

If your organization is facing a similar of issue of too much data and not enough insight, 2nd Watch can help. Our data and analytics solutions help businesses make better decisions, faster, with a modern data stack in the cloud. Contact Us to start talking about the tools and strategies necessary to reach your goals.

-Ian Willoughby, Chief Architect and Vice President

Listen to the McDonald’s team talk about this project on the 2nd Watch Cloud Crunch podcast.

Facebooktwitterlinkedinmailrss

Cloud Crunch Podcast: Data, AI & ML on Google Cloud

If you’re trying to run your business smarter, not harder, chances are you’re utilizing data to gain insights into the decision-making process and gain a competitive advantage. In the latest episode of our podcast, we talk with data and AI & ML expert, Rui Costa at Google Cloud, about why and when to use cloud data offerings and how to make the most of your data in the cloud. Listen now on Spotify, iTunes, iHeart Radio, Stitcher, or wherever you get your podcasts.

We’d love to hear from you! Email us at CloudCrunch@2ndwatch.com with comments, questions and ideas.

Facebooktwitterlinkedinmailrss

Top Enterprise IT Trends for 2021

Between the global pandemic and the resulting economic upheaval, it’s fair to say many businesses spent 2020 in survival mode. Now, as we turn the page to 2021, we wonder what life will look like in this new normalcy. Whether it is employees working from home, the shift from brick and mortar to online sales and delivery, or the need to accelerate digital transformation efforts to remain competitive, 2021 will be a year of re-invention for most companies.

How might the new normal impact your company? Here are five of the top technology trends we predict will drive change in 2021:

  1. The pace of cloud migration will accelerate: Most companies, by now, have started the journey to the public cloud or to a hybrid cloud environment. The events of 2020 have added fuel to the fire, creating an urgency to maximize cloud usage within companies that now understand that the speed, resilience, security and universal access provided by cloud services is vital to the success of the organization.

“By the end of 2021, based on lessons learned in the pandemic, most enterprises will put a mechanism in place to accelerate their shift to cloud-centric digital infrastructure and application services twice as fast as before the pandemic,” says Rick Villars, group vice president, worldwide research at IDC. “Spending on cloud services, the hardware and software underpinning cloud services, and professional and managed services opportunities around cloud services will surpass $1 trillion in 2024,”

The progression for most companies will be to ensure customer-facing applications take priority. In the next phase of cloud migration, back-end functionality embodied in ERP-type applications will move to the cloud. The easiest and fastest way to move applications to the cloud is the simple lift-and-shift, where applications remain essentially unchanged. Companies looking to improve and optimize business processes, though, will most likely refactor, containerize, or completely re-write applications. They will turn to “cloud native” approaches to their applications.

  1. Artificial intelligence (AI) and machine learning (ML) will deliver business insight: Faced with the need to boost revenue, cut waste, and squeeze out more profits during a period of economic and competitive upheaval, companies will continue turning to AI and machine learning to extract business insight from the vast trove of data most collect routinely, but don’t always take advantage of.

According to a recent PwC survey of more than 1,000 executives, 25% of companies reported widespread adoption of AI in 2020, up from 18% in 2019. Another 54% are moving quickly toward AI. Either they have started implementing limited use cases or they are in the proof-of-concept phase and are looking to scale up. Companies report the deployment of AI is proving to be an effective response to the challenges posed by the pandemic.

Ramping up AI and ML capabilities in-house can be a daunting task, but the major hyperscale cloud providers have platforms that enable companies to perform AI and ML in the cloud. Examples include Amazon’s SageMaker, Microsoft’s Azure AI and Google’s Cloud AI.

  1. Edge computing will take on greater importance: For companies that can’t move to the cloud because of regulatory or data security concerns, edge computing is emerging as an attractive option. With edge computing, data processing is performed where the data is generated, which reduces latency and provides actionable intelligence in real time. Common use cases include manufacturing facilities, utilities, transportation, oil and gas, healthcare, retail and hospitality.

The global edge computing market is expected to reach $43.4 billion by 2027, fueled by an annual growth rate of nearly 40%, according to a report from Grand View Research.

The underpinning of edge computing is IoT, the instrumentation of devices (everything from autonomous vehicles to machines on the factory floor to a coffee machine in a fast-food restaurant) and the connectivity between the IoT sensor and the analytics platform. IoT platforms generate a vast amount of real-time data, which must be processed at the edge because it would too expensive and impractical to transmit that data to the cloud.

Cloud services providers recognize this reality and are now bringing forth specific managed service offerings for edge computing scenarios, such as Amazon’s new IoT Greengrass service that extends cloud capabilities to local devices, or Microsoft’s Azure IoT Edge.

  1. Platform-as-a-Service will take on added urgency: To increase the speed of business, companies are shifting to cloud platforms for application development, rather than developing apps in-house. PaaS offers a variety of benefits, including the ability to take advantage of serverless computing delivering scalability, flexibility and quicker time to develop and release new apps. Popular serverless platforms include Amazon Lambda and Microsoft’s Azure Functions.
  2. IT Automation will increase: Automating processes across the entire organization is a key trend for 2021, with companies prioritizing and allocating money for this effort. Automation can cut costs and increase efficiency in a variety of areas – everything from Robotics Process Automation (RPA) to automate low-level business processes, to the automation of security procedures such as anomaly detection or incident response, to automating software development functions with new DevOps tools.

Gartner predicts that, through 2024, enhancements in analytics and automatic remediation capabilities will refocus 30% of IT operations efforts from support to continuous engineering. And by 2023, 40% of product and platform teams will use AIOps for automated change risk analysis in DevOps pipelines, reducing unplanned downtime by 20%.

Tying it all together

These trends are not occurring in isolation.  They’re all part of the larger digital transformation effort that is occurring as companies pursue a multi-cloud strategy encompassing public cloud, private cloud and edge environments. Regardless of where the applications live or where the processing takes place, organizations are seeking ways to use AI and machine learning to optimize processes, conduct predictive maintenance and gain critical business insight as they try to rebound from the events of 2020 and re-invent themselves for 2021 and beyond.

Where will 2021 take you? Contact us for guidance on how you can take hold of these technology trends to maximize your business results and reach new goals.

-Mir Ali, Field CTO

Facebooktwitterlinkedinmailrss

Cloud Crunch Podcast: How McDonald’s France is Using Data Lakes to Improve Customer Experience

Adrien Sieg, Head of Data at McDonald’s Global Technology France, Christina Moss, Director of AWS Cloud Services at McDonald’s, and Mathieu Rimlinger, Director of Global Technology France at McDonald’s, talk about their latest technological advancements in the cloud and how McDonald’s is using data lakes to set customer expectations and improve satisfaction. Listen now on Spotify, iTunes, iHeart Radio, Stitcher, or wherever you get your podcasts.

We’d love to hear from you! Email us at CloudCrunch@2ndwatch.com with comments, questions and ideas.

Facebooktwitterlinkedinmailrss