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From print-outs on a bulletin board to fully automated lifecycle dashboard, Interloop® helps leading manufacturer go from data-dark to sights on the stars. OUR CLIENT Founded in 1951, this family-owned, operated venture designs and produces premier pyrometers with innovative wavelength selection that can accurately view through common industrial interferences including steam, flames, combustion gasses, water, plasma and oil. Industry leaders for 70+ years, our client proudly serves manufacturers across the globe with thousands of successful installations spanning steel, incineration, glass, CVD/semiconductor, aluminum and petrochemical spaces. THE CHALLENGE Answering critical business questions meant accessing multiple systems, manually downloading reports, and manipulating data. This cumbersome process drained significant time, effort and resources for straightforward questions that required quick answers. As their operations continued to scale internationally, this manufacturer knew it needed faster, automated reporting with reduced risk and margin for error. ENGAGE - THE FIRST MISSION From data-dark to shoot for the moon Interloop's first task was to develop a resource for our client’s business development team to track their progress and goals. This resource supported sales leadership in conducting one-on-one review sessions, forecasting sales, increasing pipeline visibility, and managing customer/account health. Data-curious and two steps ahead on prep-work, our client had already started consolidating data from different systems into one place - bringing data from their ERP, CRM and financial systems into Microsoft Access. With a clear runway, Interloop leveraged our proprietary FastDash process to design and develop a comprehensive sales dashboard customized to suit. Once live, our client immediately enjoyed near real-time insight and instantly realized the potential for more. Onward. They asked the Loopers to move from business development to providing insights on production and shipment including: Optimizing technician and assembler load balancing post-order. Predicting order delivery timelines and managing their distribution. Assessing if the order backlog could meet goals. Identifying the most and least productive technicians and assemblers. Determining which items could be delivered early to expedite invoicing. “I can’t believe how far we’ve come since starting this project.” EXPAND - THE SECOND MISSION Sights set on the stars with a Full Lifecycle Dashboard Interloop's next mission involved integrating production and shipment metrics for what would become a Full Lifecycle Dashboard. This robust enhancement provided our client with a comprehensive view of their business from sales through to production and shipment. Building on our solid foundation, we curated a fully automated Lifecycle Dashboard that spans sales, production, and shipment information - updated 8x per day, it provides near real-time insight into critical business functions. Additionally, PDF versions select dashboard pages are sent out once a week via email to designated members of the company to communicate the company’s performance. What used to take hours to export, compile, and format data to create these summary reports to share amongst leadership, now takes less than 5 minutes. “We went from a bulletin board with printed reports to a real time view displayed on a screen in the lab.” SKY IS THE LIMIT Growing Together, Celebrating Wins For us, this story is really the ideal evolution of a collaborative, curious client who came to us open and eager to expand potential and achieve more with their data. Starting from printed reports pinned to a bulletin board, our client now works from near-real time insights consistently communicated with automated distribution. What began as a singular department’s sales dashboard has since evolved into a true Mission Control platform leveraged daily to confidently across executive leadership to run and scale their venture. Today, Interloop is proud to continue supporting our client through iterations and enhancements to their Full Lifecycle Dashboard along with exploring options for migrating data into a more future-proof system that is cloud-based tomorrow. Interloop is a Microsoft ISV Partner at the forefront of helping manufacturing businesses across the country achieve more with their data. Ready to achieve more with your data? Let’s loop you in. Book your intro call with our data experts today.

Author: Will Austell When it comes to Customer Relationship Management (CRM) systems, maintaining data integrity is paramount. However, even with robust structures in place, challenges arise, such as the existence of orphan records. Stay with us as we delve into a practical solution based on a real client’s scenario using Python and SQL within a CRM's account module. The Challenge: Orphan Ship-To Accounts Interloop is working with a client that has a CRM system where accounts are categorized into Bill-To and Ship-To accounts, forming a parent-child hierarchy. Ideally, Ship-To accounts should always have a corresponding Bill-To parent. However, orphan Ship-To records, those without a Bill-To parent, can occur due to system limitations or human error. The Solution: Fuzzy Address Matching To address this challenge, Interloop proposed a solution leveraging Python's rapidfuzz library for fuzzy string matching and SQL for data manipulation to connect these orphan Ship-To records to an existing Bill-To parent record based on address matches. We will be working in a Spark notebook in Microsoft Fabric. Here's how it works: 1. Installing and Setting Up RapidFuzz First, we install the Rapidfuzz library, a powerful tool for string matching and similarity measurement, via pip. 2. Data Retrieval and Preparation We retrieve relevant data from the CRM database using SQL queries, focusing on Ship-To and Bill-To accounts within a specific region (e.g., EDOH in this example). These queries yield dataframes in a Spark environment, which we subsequently convert to Pandas dataframes for local processing. 3. Address Normalization Before comparison, we normalize the addresses of both Ship-To and Bill-To accounts by concatenating relevant address fields and applying lowercase conversion, stripping, and removal of non-alphanumeric characters. This step ensures uniformity for accurate matching. 4. Fuzzy Matching Using RapidFuzz, we iterate through each Ship-To and Bill-To pair, calculating a similarity score based on their normalized addresses. A threshold of 87% is set to consider matches, ensuring a balance between precision and inclusivity. The score threshold will vary and can be calibrated to meet your specific string-matching needs. In our example, we found the sweet spot was around 87% for optimal address matching. 5. Storing Matched Results Fuzzy matched results are stored in a delta table, preserving essential details such as IDs, account types, and dates entered. This structured storage facilitates further analysis and action. 6. Selecting Optimal Matches To mitigate redundancy, we select the highest scoring match for each Ship-To account, discarding lower-scoring alternatives. This step ensures the accuracy and efficiency of the matching process. Conclusion Incorporating fuzzy address matching into CRM data management workflows offers a pragmatic approach to address integrity challenges. By leveraging Python's rapidfuzz library and SQL for data manipulation, organizations can enhance the accuracy and completeness of their account records, thereby improving decision-making and customer service. In summary, through the integration of advanced matching techniques, the vision of a harmonized CRM dataset—free from orphan records—is within reach, ushering in a new era of data integrity and operational efficiency. Looking for clear, practical solutions to your data challenges? Let’s loop you in. Book your intro call with our data experts today.

Author: Anna Cameron Leveraging data for decision making begins with connecting to relevant data. However, what seems straightforward often proves to be complicated and time intensive. Factors like data volume, disparate data repositories across different platforms, and the lack of seamless data integration between different platforms can intensify the complexities that come with harnessing business data. More so, once data is cleaned, migrated, and accessible, it’s important to determine which type of connection is optimal for the given task. Here’s where Microsoft Fabric comes in. Microsoft Fabric offers a comprehensive suite of tools to streamline data connectivity and analysis. The selection of an appropriate method starts with understanding each method's strengths and limitations to ensure the best outcomes for diverse analytical scenarios. The three primary methods that can be used in Power BI include Import, DirectQuery, and the DirectLake. Each method carries advantages and drawbacks, so it’s essential to understand them all to see which aligns with your given analytics task. Import Importing data directly into a Power BI file is a relatively quick process that is conducive for smaller datasets. However, efficiency is tempered by its inability to sync real time data. The import process copies data tables from the lake house or warehouse and saves them in the Power BI file itself. Any modifications to the data source require manual importing of the data to reflect the changes in Power BI. To mitigate this limitation, scheduled refreshes can be used to ensure that data in the Power BI file is current. DirectQuery DirectQuery in Power BI offers a direct connection to the necessary data source which maintains data integrity and almost real-time data synchronization. Despite these advantages, this method encounters a performance trade off in slower analytics, particularly in scenarios with complex DAX calculations. DirectQuery functions by executing queries in the data source’s semantic model to retrieve data that fits the provided query. For example, a DAX query would be translated to a SQL query format to be run in the data source level. The result of that SQL query is then sent back to Power BI report where it can be used in a KPI visual. DirectQuery finds its niche in scenarios using large data sets where near real time data is more important that swift analytic processing. DirectLake DirectLake is a novel approach to data connection in Power BI. It essentially combines the advantages of import and DirectQuery while mitigating the respective limitations. By using parquet files sourced from Microsoft OneLake, DirectLake eliminates the need for query translation and bypasses the conventional data import, providing accelerated data access. Moreover, like DirectQuery, DirectLake ensures near real time data synchronization, making it a preferred choice for large data models where data changes frequently. Conclusion Using big data for decision making may be complex in business environments, but Power BI offers several techniques to make this possible by connecting through Import, DirectQuery + the DirectLake. Each method has its own advantages and limitations. Import mode is a relatively quick solution best for smaller data set, but is accompanied with the possibility of data staleness. On the other hand, DirectQuery and DirectLake are robust options for analysis of large data models where the analytics need to stay synced with changes in the data source. While DirectQuery can be a slightly faster method as it offers direct connectivity, it comes with the expense of slower analytics due to the need to translate queries between the data source and the Power BI file. DirectLake is a promising alternative that combines the strengths of import and DirectQuery while circumventing the need to translate queries. Ultimately, choosing the best connection method hinges on the specific requirements and nuances of the analytical task, ensuring that data-driven decisions are both informed and agile in response to dynamic business landscapes. Need help understanding and identifying which method is best for connecting your data with Power BI & Microsoft Fabric? Let’s loop you in. Book your intro call with our data experts today.

In the ever-evolving landscape of data analytics and business intelligence, staying ahead means leveraging the most advanced tools available. Microsoft Fabric emerges as a beacon for enterprises seeking to harness the full potential of their data. As a proud Microsoft partner, we're excited to guide you through the process of starting your free trial with Microsoft Fabric, ensuring you can explore its vast capabilities firsthand. Why Microsoft Fabric? Microsoft Fabric represents a significant leap forward, offering an all-encompassing analytics solution. From seamless data movement to sophisticated data science, real-time analytics, and comprehensive business intelligence, Fabric provides a unified platform to address all your data needs. What sets Fabric apart is its integration with Power BI, enhancing the analytics experience with advanced features and capabilities. Starting Your Journey with Microsoft Fabric Embarking on your Fabric trial is straightforward, whether you're an existing Power BI user or new to the ecosystem. Here's how: For Existing Power BI Users If you're already familiar with Power BI, you're one step ahead. Jump straight into the Fabric trial to unlock the additional features and experiences it offers. New to Power BI? No worries! The first step is to secure a Power BI license, which is effortlessly done by visiting the Fabric sign-up page. This initial step ensures you have access to the foundational tools necessary for your journey with Fabric. Initiating the Fabric Trial 1 - Visit the Fabric Homepage: Navigate to the Fabric platform and access the Account Manager. 2 - Start Your Trial: Look for the "Start Trial" option. If it's not visible, it may be temporarily disabled for your organization. 3 - Agree to Terms: Follow the prompts, agree to the terms, and kick off your trial. 4 - Confirmation: Once set up, you'll receive a confirmation. Now, you're ready to dive into the Fabric experience. 5 - Monitor Your Trial: The Account Manager will help you keep an eye on your trial duration, ensuring you make the most out of your experience. Tailoring the Experience At Interloop, we understand the significance of data analytics in driving business success. Our partnership with Microsoft enables us to offer unique insights and support as you explore Fabric's capabilities. Whether you're looking to enhance your data analytics practices or explore new business intelligence horizons, our team is here to guide you every step of the way. Conclusion Microsoft Fabric offers a golden opportunity to elevate your data analytics capabilities. By starting your free trial today, you're not just accessing a powerful tool; you're opening the door to a future of data-driven decision-making and strategic insights. Dive in, explore, and let's harness the potential of your data together. Interloop is a Microsoft ISV Partner at the forefront of helping organizations achieve more with their data. Leveraging the best in data technology, Interloop can help you get started with Microsoft Fabric. Curious how your organization could benefit from using a tool like Fabric? Let’s loop you in. Book your intro call with our data experts today. Looking to learn more? Join us for Microsoft Fabric: Bring Your Data Into The Era Of AI - a free webinar on March 7 at 11AM EST. Save your seat today.

Interloop Founders Jordan and Tony Berry explore all things Microsoft Fabric starting with defining and identifying its key features spanning data engineering, Power BI, data factory, data warehouse, real-time analytics and data science. In the realm of technology, Microsoft is a name that commands recognition and respect on a global scale. With a reputation built on consistently providing reliable, innovative, and user-friendly products, they have cemented their status as a leading player in the sector. Microsoft's array of software solutions, ranging from operating systems to productivity tools, are an integral part of the infrastructure for businesses and individuals alike. Microsoft Office, for instance, is a ubiquitous tool that has shaped the modern workforce. In this ever-evolving technology landscape, Microsoft continues to innovate and introduce new offerings that are designed to meet the changing needs of businesses. One of their recent introductions is Microsoft Fabric. Fabric isn't just another product; it marks a new direction in Microsoft's approach to offering flexible, scalable, and efficient cloud-based services and applications. As businesses grapple with ever-increasing volumes of data, the need for tools and technologies that can help manage, analyze, and act on this data in real-time becomes more critical. Fabric is designed to address this need. Understanding what Fabric is, and more importantly, why it should matter to your business, is essential. This new offering from Microsoft is poised to redefine how businesses manage and interact with their data, offering a suite of technologies and practices that promise to make data handling more efficient and insightful than ever before. Whether you're a small business owner looking for ways to leverage your data more effectively, or a key decision-maker in a larger organization seeking to harness the power of your data repositories, Fabric deserves your attention. It represents a significant step forward in Microsoft's commitment to providing cutting-edge technological solutions that empower businesses and individuals to achieve their goals. What is Microsoft Fabric? Microsoft Fabric is more than just a single product or application. In essence, it’s a collective term used to represent a comprehensive suite of innovative technologies, meticulous strategies, and best practices that are employed by Microsoft. The underlying objective of Fabric is to design resilient, scalable, and efficient cloud-based services and applications to meet the evolving needs of businesses. At the core, Fabric is the harmonious cooperation of several potent Microsoft tools namely: Power BI, Azure Synapse, and Azure Data Factory. These robust programs operate in perfect synchrony to create a reliable and highly responsive infrastructure. This infrastructure is equipped to assist businesses of all scales in efficiently storing, analyzing, and acting on their gigantic data repositories. Being an integral part of the extensive Microsoft ecosystem, Fabric users are provided with a highly integrated, end-to-end, and user-friendly product. The design of Fabric is simple yet effective, aiming to simplify the analytics needs of businesses and bring all their data into one centralized space. Primary Solutions from Microsoft Fabric include: An extensive range of deeply integrated analytics, which serve as the industry benchmark A unified, intuitive interface that spans across all components, enhancing the user experience Easy access to use and reuse preexisting assets, ensuring optimal utilization of resources Data storage in a unified data “lake”, providing seamless access to analytics tools Streamlined administration and governance with centralized management, improving operational efficiency To put it in simpler terms, Fabric is a tool that empowers organizations, especially those dealing with massive amounts of data, to compartmentalize, organize, and analyze their data in a manageable and effective manner. The specifics of how Fabric achieves this is a complex process and warrants a more detailed and in-depth breakdown. Key Features of Microsoft Fabric Data Engineering – Fabric offers a world-class Spark platform with excellent authoring experiences. This enables data engineers to perform large-scale data transformations and democratize data through the lake house. The integration of Microsoft Fabric Spark with Data Factory allows for scheduling and orchestration of notebooks and spark jobs. Power BI – Power BI provides business owners with quick and intuitive access to all the data in Fabric. It features user-friendly visualizations and dashboards. Its integration with Fabric, Azure Data Lake Store, Azure SQL DB, and Machine Learning Services makes it one of the most comprehensive analytics platforms on the market. Data Factory – Azure Data Factory combines the simplicity of Power Query with the scale and power of Azure Data Factory. It offers 200+ native connectors for linking to data sources both on-premises and in the cloud. Data Warehouse – The Data Warehouse feature delivers top-tier SQL performance and scalability. It effectively separates compute from storage, allowing independent scaling of each component. Plus, it natively stores data in the open Delta Lake format. Real-Time Analytics – This feature handles observational data collected from diverse sources such as apps, IoT devices, and human interactions. As this data is typically semi-structured (like JSON or Text) and arrives in high volumes with constantly changing schemas, traditional data warehousing platforms often struggle to manage it. Real-Time Analytics provides an effective solution. Data Science – Fabric allows for the seamless building, deployment, and operationalization of machine learning models. Integrated with Azure Machine Learning, it offers built-in experiment tracking and model registry. Data scientists can enhance organizational data with predictions, which business analysts can incorporate into their BI reports, thus shifting from descriptive to predictive insights. The Business Impact of Microsoft Fabric Advancement in Application Development: As organizations progressively embrace microservices-based structures for modern application development, Fabric's suite of tools and technologies, including Azure Service Fabric and AKS, become indispensable. They are pivotal for developers who are focused on building applications that are cloud-native and microservices-oriented. Emphasis on Scalability and Reliability: Microsoft Fabric's commitment to scalability and reliability is a critical aspect for businesses that need to ensure their applications can accommodate increasing workloads and maintain operational continuity. This is particularly vital for sectors such as e-commerce, finance, and healthcare, where downtime can have substantial implications. Streamlined Management: Azure Service Fabric and AKS offer a simplified approach to both data management and compartmentalization, reducing the operational load for development teams. This empowers them to concentrate on introducing value-added features instead of managing the intricate details of the overarching data infrastructure. Hybrid Cloud Compatibility: Designed to operate seamlessly in hybrid cloud environments, Microsoft Fabric holds significant value for organizations planning to utilize both on-premises and cloud resources. This is a particularly crucial feature in the current era, where remote work is increasingly common. Superior Large-Scale Data Management: Handling big data at a large scale can be daunting, perplexing, and quite challenging to navigate effectively. However, with Fabric’s data management capabilities, businesses can rest assured of their ability to work with critical information efficiently. In the realm of business technology, maintaining control over data is paramount to the success of an organization. Inability to access or manage that data effectively can lead to significant operational challenges, particularly for companies handling large volumes of data. The complexity of "Big Data" can be daunting, underscoring the need for tools like Fabric. Fabric assists users in deciphering and breaking down crucial metrics, enabling teams to make informed decisions based on comprehensive data, rather than just the portions they can readily comprehend. Interloop is a Microsoft ISV Partner at the forefront of helping organizations achieve more with their data. Leveraging the best in data technology, Interloop can help you get started with Microsoft Fabric. Curious how your organization could benefit from using a tool like Fabric? Let’s loop you in. Book your intro call with our data experts today. Looking to learn more? Join us for Microsoft Fabric: Bring Your Data Into The Era Of AI - a free webinar on March 7 at 11AM EST. Save your seat today.

Allow us to reintroduce ourselves… For the past 5 years, Interloop has empowered organizations to achieve more with their data. Today, we are proud to enter a new era for both our company and our data-driven clients across the country. Announcing Insights Automated™, a new approach for unifying & gaining insights from your data fueled by Microsoft Fabric. Interloop is ready to help mid-market companies reach new levels of insight and impact. It’s all systems go. And we’re just getting started. The Data Landscape Has Changed The world looks different since we started. The modern data platform entered the scene and enabled us to unify data through a central hub streamlining a simplified path to key insights. Technologies like Databricks, Snowflake, Azure Synapse and more proved that a centralized data approach could create increased agility and impact for organizations. As a Microsoft ISV Partner, Interloop earned early access to the newly unveiled Microsoft Fabric, a “OneDrive” for data and seismic shift in the data landscape. By building on top of this all-in-one platform, Interloop Mission Control will provide a centralized hub for gaining insights and making better decisions faster. This will allow our clients to gain a competitive advantage using the data assets they already own. Your Data Driven Guides What makes the Interloop Way different? Rather than simply providing a tool or standalone recommendations - we focus on creating a holistic solution that drives real impact. Whether you come from Manufacturing & Distribution, Retail & Consumer Goods, Financial Services or the vast spaces between, we meet you where you are today so we may grow with you tomorrow. With our renewed focus, Interloop is expanding our partnerships, team and capabilities to better serve our clients each and every day. Whether they are working to drive growth, reduce costs, gain visibility or make the most of their existing investments - we are here to help you harness and leverage your data to save, scale, safeguard and, ultimately, succeed in your business. Here’s What To Expect From Us You’ll see exciting updates and additions from Interloop in the coming weeks: Expanded Partnerships: We’re all in on our partnership with Microsoft, we just launched Interloop on the Azure Marketplace and strive to be the leading AI & Data Partner in the Southeast & beyond. Thought Leadership: Stay tuned for our Fueled By Fabric webinar coming in October where Loopers will share insights on this innovative new technology and how it can impact your data strategy. Events: We’ll be attending and hosting a full calendar this fall to include sponsoring the SC Manufacturers Expo November 9th-10th. If you will be in attendance, or happen to swing by the Charleston Digital Corridor - please stop by and say hello! Interloop.ai is now Interloopdata.com - Moving forward, all communication and outreach will come from this updated domain. While we will continue to focus on our AI & predictive offerings and associated data engineering as a service solutions, this new domain better encompasses our mission and trajectory. Designed by The Cohort Collab, our refreshed digital hub will host industry insights, resource libraries, thought-leadership, events and more. With You From Insight To Impact As your data partner, our sights are set on the stars and shared success. This renewed mission will enable us to empower organizations like yours to leverage data & predictive analytics like never before. We can’t wait to embark on this mission together. Tony Berry, CEO & Co-Founder of Interloop Jordan Berry, CTO & Co-Founder of Interloop Get Looped In Based in Charleston, SC and serving mid-market companies nationwide, Interloop™ is the Microsoft ISV partner and premier data engineering firm taking emerging entities from data-dark to insight and impact. Integrating people, process and technology, we equip the data curious across industries with a single solution to centralize, organize and act on labyrinths of specialized, siloed and disconnected data sets and services. Powered by Microsoft’s Azure’s comprehensive cloud computing platform and at the forefront of AI with Microsoft Fabric, achieve more with your data. Get looped in or take our 15-minute self assessment today.

In today’s world, we’re awash with a deluge of data - constantly being generated from the devices we use, the systems we build, and the interactions we have. Organizations across every industry are using this data to fuel digital transformation and gain a competitive advantage. Pair this with the emergence of cutting age technology like generative AI - data, and becoming Data-Driven is more important than ever. And yet, this data is often stratified, disconnected, siloed, and difficult to use - meaning most organized are leaving a highly strategic asset on the shelf. It requires new end-to-end tools and a proven approach to activate this data in a way that generate tangible value for the business. That’s why leveraging a human-centered analytics product like Microsoft Fabric, backed by the proven strategies and tactics used across dozens of clients at Interloop is imperative to capturing this opportunity. Struggling to deal with the complex data environment? You’re not alone. Organizations are facing an array of data challenges today such as: Scaling Data & Analytics across the organization while reducing costs & optimizing existing data and management Gaining Business Intelligence Adoption to streamline data usage and insights across departments Encouraging data literacy by making data more accessible and easier to understand by both technical and non-technical team members Balancing the need for governed and self-service data exploration and analytics Limited scalability of legacy solutions while demand from the business explodes Breaking down data siloes across the various departments and functions of the business Delivering on the promise of automated insights with limited resources Like most complex challenges, investing in People, Process, & technology through training, tooling, and a proven approach is essentials to avoiding failed data initiatives. Best of Breed vs All-In-One, which approach is best for my organization? If you search for “Modern Data Platforms”, often times the first result will include an architecture diagram that looks something like this: Building, maintaining, and encouraging adoption of a Modern Data Platform can be a steep learning curve for most organizations but those that are able to overcome this challenge are likely to benefit greatly. If you break it down, there are several key components that make up a modern data platform approach. Connection & Extraction In order to analyze your data, you need to be able to connect to the various cloud applications, databases, file storage, and streaming data sources that generate the data. A modern data platform needs to manage the access credentials and keep open live connections to these data systems. From there, it needs to be able to extract the data into a centralized location - often called the data lake. While some approaches such as Data Virtualization or Zero ETL work to remove any copying of data, in practice - we’ve found that landing a raw copy of the data allows for the most downstream use cases. Example best of breed tools include: CData, Fivetran, Funnel.io, etc Organization & Modeling Once the data has been landed into the Lakehouse, there is work to be done to standardize, organize, and model the data. Example Tools Include: DBT, Transform, Data Bricks, etc Consumptions & Activation Ultimately, being able to make better decisions faster is the key outcome of leveraging Example Tools Include: PowerBI, Tableau, High Touch, Census Governance While entropy, or the idea that all things fall into chaos if not maintained - is just as relevant in Data as it is in physics. Organizations must work to maintain, document, and promote datasets in order to drive adoptions across the organizations. Companies will also need to be very mindful of the contents of this data and the sensitivity of the data. This often means auditing for PII (Personally Identifiable Information) and ensuring that the stricture of data privacy laws such as GDPR & CCPA are being upheld. The MAD (Machine Learning, AI, & Data) Landscape in 2023 An average modern data platform consists of 8 or more tools that must work in harmony to create the desired outcome. For many organizations, this means 8 different contracts with different payment terms, limitations, and usage. Combine this with the need to train your team on the nuances of each tool, the modern data platform approach, and the data systems and processes of your organization - this can often become overwhelming. Example Tools Include: Secoda, To view a full list of tools available in the MAD (Machine Learning, AI, & Data) Landscape - check out this great visual by Matt Turck - https://mattturck.com/mad2023/ Introducing Microsoft Fabric, a unified SaaS-based solution for data & analytics Microsoft Fabric combines several of Microsoft’s flagship data products such as Data Factory, Synapse Analytics, Data Explorer, and Power BI into a single, unified experience, on the cloud. The fabric platform is a cost-effective and performance-optimized fabric for business intelligence, machine learning, and AI workloads at any scale. It is the foundation for migrating and modernizing existing analytics solutions, whether this be data appliances or traditional data warehouses. By establishing connectivity and integration, organizations can transform their unstructured and siloed data into a valuable strategic asset through: Data modernization backed by the Microsoft Azure Cloud Cloud-native applications at any scale Responsible, powerful AI to make more informed decision-making Analytics and insights at a faster rate Responsible for machine learning and artificial intelligence Governance backed by Microsoft Purview As we all know, powerful tools don’t solve organizational challenges on their own. It takes a strategy, expertise, and the ability to execute in order to harness the value of any platform. That’s where Interloop comes in - we bring our proven approach, deep expertise, and a team of capable data engineers, data analysts, data scientists, and delivery managers to ensure you achieve a successful data initiative. Solving complex data and analytics challenges with Fabric & Interloop Data is inherently agnostic but can be used in distinct ways based on your business function & use case. Here are a few examples of how you can use data to optimize your organization. Marketing Improve Campaign Analysis & Planning Optimize Paid Media spend & activation Perform unified website, social, & email analytics Sales Identify better opportunities for upsell & cross sell Develop enhanced quoting & pricing plans Improve sales performance through analysis Operations Optimize Production & Delivery Enhance Inventory Planning & Performance Streamline fullfillment & distribution People Reduce employee turnover & improve retention Gain visibility into recruiting & performance Monitor benefits, rewards, and compensation The art of the possible Your customers, employees, partners, and suppliers likely have unmet needs that could be uniquely solved by combining your business strategy with unified data, comprehensive insights, and faster decision-making. Ready to begin your journey, let us loop you in by having a conversation with an expert today.

Microsoft Fabric makes setting up & managing your data platform simpler than ever. Combined with Interloop’s team of experts, you can transform data into insights faster than ever. What is Microsoft Fabric? At Microsoft Build 2023, Satya Nadella introduced Fabric, Microsoft’s unified SaaS-based solution that stores all organizational data. Microsoft fabric combines many of their existing tools, Data Factory, Synapse Analytics, Data Explorer & Power BI into a single unified experience. This is all built on top of an open and governed lakehouse foundation layer - introduced as One Lake. The goal of fabric is to create a cost-effective & performance-optimized toolkit that can be used for all things data. This includes running adhoc queries, business intelligence workload, AI & machine learning, & much more. This cloud native offering, handles much of the complexities & technical hurdles that have historically plagued data engineering teams such & creates a single location for an organization to operate their data workloads - regardless of the use case. While this tool has dramatically lowered the barrier to entry, it does still require expertise to operationalize effectively. We’re optimistic that this set of tools will help data teams across the globe deliver more value to those how needs insights to operate their organizations. One Lake: It’s like OneDrive for your Data One of the biggest challenges when trying to build a modern data platform for your organization is copies of data everywhere. You need to manage the data in your operational systems, copy it into your data lake, and then possibly copy the data again into your data warehouse. If you need to share data or access data from a third party, more copies. OneLake aims to solve these challenges for an organization. As Microsoft states: OneLake is a single, unified, logical data lake for the whole organization. Like OneDrive, OneLake comes automatically with every Microsoft Fabric tenant and is designed to be the single place for all your analytics data. Why is this a game changer? By unifying data at the highest level, organizations can finally leverage data as a competitive advantage. Cross functional teams can all operate off the same underlying source of truth to make decisions faster. Combine this with a singular governance model that allows different domains in the business to operate in concert with each other at each step of the way - this is a truly revolutionary approach to data management. What are Shortcuts? In addition to OneLake, Microsoft introduced Shortcuts - a way to connect & analyze data across different business domains (or even other organizations) without having to move the data. For those that are familiar with the promise … and shortcomings, of Data Virtualization — this appears to be a monumental step towards a Zero ETL (LINK) world. Let’s paint this picture a little more vividly - imagine your organization works with Channel Partners that each collect data that needs to be analyzed. Some store it in ADLS, Microsoft’s Storage Layer while others have adopted Amazon’s S3 Storage tools. With Shortcuts, this data can all be analyzed without having to setup any ETL pipeline to consolidate this data into one analytical Store. We’re excited to see the developments with shortcuts but in theory this will open up the ability to share data within & across organizations in wholly novel ways. What happened to Azure Synapse? For those familiar with Microsoft’s analytics offerings - you may be wondering “So what’s going to happen with Azure Synapse?” Microsoft has stated that while Azure Synapse Analytics will remain available to customers, most of the R&D resources will be moving toward Fabric. Reading between the lines, we would expect that the Azure Synapse Studio will not see many updates over the coming months while most of the functionality is moved into Fabric. One of the biggest changes when moving to Fabric is that Microsoft does not intend to move Mapping Data Flows into Fabric. If your organization currently uses MDF, you will need to re-evaluate your approaches to data transformation. Our advice, continue using Azure Synapse Analytics in tandem with Microsoft Fabric until it is available through general availability near the end of 2023. How do I get started with Microsoft Fabric? In an effort to drive organizations to try out Microsoft Fabric, Microsoft is offering a Free trial. You can simply navigate to your existing PowerBI Instances and you will see a new Fabric Branded portal. To navigate directly to Microsoft Fabric - visit https://app.fabric.microsoft.com/ Microsoft Fabric is in Public Preview with General Availability expected to be available near the end of 2023. Should I migrate to Microsoft Fabric? With all these additional capabilities, should you migrate everything to Fabric today? After using Fabric for several weeks, we would recommend the following approach: 1. For production workloads, continue to use Azure Synapse Analytics over Microsft Fabric. We’ve noticed that there are definitely some bugs and shortcomings with the Fabric Interface at the moment (as of publishing this article in August 2023. We expected Microsoft to address many of these challenges in the coming months) → LINK OR EMBED TO FABRIC ISSUE TRACKER Check out our Microsoft Fabric Issue Tracker to a list of shortcomings or challenges our experts have experienced while working with Microsoft Fabric. 2. Adopt the Microsoft Fabric Lakehouse Structure (Files & Delta Tables) Today By adopting the new Microsoft Fabric Lakehouse Standard, organizations can prepare themselves for a smooth migration down the road. By standardizing on Delta Tables, we’ve seen many organizations achieve speed gains, a shared understanding, & technical benefits such as full ACID transaction support an more. To learn more about the benefits of the Delta Table, open source format - Read this article by Data Bricks. 3. Take advantage of the Free Trial to find any data gaps With Microsoft offering a generous free trial, we advise our clients to begin experimenting with Microsoft Fabric to better understand it’s limitations, the capacity pricing model, & new functionality (such as the recently launched Data Activator). If you are already using PowerBI, you’ll be very familiar with the concepts and should be 4. Get Started Experimenting Today Microsoft has made it clear that Fabric is the Future so by experimenting or working with experts today, you’ll be ahead of the curve when Fabric becomes the standard for most Microsoft Based organizations. To learn more about migration specifics & how your organization should think about a transition to Microsoft Fabric - read our Migration Guide: From Azure Synapse Analytics to Microsoft Fabric (LINK TO BLOG) How do I get started today? Schedule a free consultation with one of our experts to understand how you can start using Microsoft Fabric Today.