Hi [[ session.user.profile.firstName ]]

How SPAR Created a CPG Sales Data Exchange with Data Preparation

SPAR is one of the world’s largest food retailers operating more than 13,000 stores in 48 countries across the globe. To understand sales trends, market conditions and the performance of different promotions, SPAR relies on data shared by their retailers and their own ability to analyze that data. You can imagine this isn’t easy!

Comparing data across their vast network of retailers means that SPAR’s analytics team has to standardize data across different languages, currencies, formats and product hierarchies. Talk about a data wrangling challenge!

Join this webinar to learn how SPAR utilized Trifacta’s data preparation platform to turn this massive data headache into a competitive advantage for their business. SPAR’s Head of International Operations, Tom Rose and Lead Data Analyst, Dharshini Manoharan will dig into the following topics during this webinar:

● How SPAR created a strategy to turn data bottlenecks into analytic opportunities
● What technology, people and process components were required for success
● Who utilizes data preparation within SPAR and where it fits in their tech stack
Recorded Jan 19 2021 51 mins
Your place is confirmed,
we'll send you email reminders
Presented by
Tom Rose, SPAR International | Dharshini Bhuvaneswari, SPAR International | Andy Steed, Big Data LDN
Presentation preview: How SPAR Created a CPG Sales Data Exchange with Data Preparation

Network with like-minded attendees

  • [[ session.user.profile.displayName ]]
    Add a photo
    • [[ session.user.profile.displayName ]]
    • [[ session.user.profile.jobTitle ]]
    • [[ session.user.profile.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(session.user.profile) ]]
  • [[ card.displayName ]]
    • [[ card.displayName ]]
    • [[ card.jobTitle ]]
    • [[ card.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(card) ]]
  • Channel
  • Channel profile
  • Self-Service Product Analytics in Practice Mar 18 2021 2:00 pm UTC 60 mins
    Jeff Sloan, Data Product Manager, Treatwell | Andy Steed, Big Data LDN
    You need product analytics. Practically every blog post is telling you that you should inform your product roadmap with data. However, the Medium posts and technology vendors don't tell you that product analytics is a cross-functional discipline. Using data for product decisions involves developing reliable business, technology, and devops competencies to turn data into insights. In this talk, Jeff Sloan will explore how Treatwell has taken a decentralized approach to product analytics, and how Snowplow Analytics enables Treatwell's product teams to self-serve their event tracking, reporting, and product analytics needs.

    Speaker: Jeff Sloan, Data Product Manager at Treatwell
  • Dealing with Data Sovereignty at Scale Recorded: Mar 4 2021 56 mins
    Budha Bhattacharya, Evangelist at Tyk and Andy Steed, Content Director at Big Data LDN
    Data sovereignty, the concept that data is subject to certain laws, usually specific to geographies, is becoming more of a challenge for businesses as they scale across regions. However, compliance considerations apply not only to data at rest but also in transit. With consumer awareness growing, failure to meet compliance requirements can lead to huge negative implications to the finance and reputation of your businesses.

    Join us for a panel discussion:
    - What are some of the challenges businesses are facing with regards to data sovereignty?
    - How do you set up and manage your data as you scale across regions?
    - What tools and techniques can help businesses handle such an expansion while staying compliant?
    - How is Tyk enabling organisations to be compliant with data sovereignty rules across regions?

    Speakers:
    Budha Bhattacharya, Evangelist at Tyk and Andy Steed, Content Director at Big Data LDN
  • Smarter AI with Analytical Graph Databases - Best Practices and Case Studies Recorded: Feb 23 2021 59 mins
    Victor Lee, Head of Product Strategy & Developer Relations, TigerGraph | Andy Steed, Big Data LDN
    Today's analytical graph databases are taking organisations to another level by connecting all their data, representing knowledge better, and obtaining answers to deeper questions in real-time.
    These benefits extend to the world of machine learning and AI. This talk will illustrate several ways in which graph databases and graph analytics can deliver smarter AI:
    • Unsupervised learning with graph algorithms
    • Feature extraction and enrichment with graph patterns
    • In-database ML techniques for graphs

    Join us as we share client case studies from 7 out of the top 10 banks in the world, China Mobile, Xandr (part of AT&T), UnitedHealth Group, and Intuit Corporation. We will cover use cases including entity resolution, customer 360, recommendations, and real-time fraud detection.
  • How to Build a Successful DataOps Program Recorded: Feb 16 2021 60 mins
    Chris Bergh, Founder, CEO & Head Chef at DataKitchen | Andy Steed, Big Data LDN
    The organizations that adopt DataOps produce robust and accurate analytics more rapidly than their peers, powering strategic decision making that gives them a significant competitive advantage. Although many companies recognize the benefits of DataOps, many struggle when it comes to building their own program. The options are to build a DataOps solution using multiple DevOps and workflow tools, or to adopt a DataOps Platform. In this webinar, we outline the key components needed for a successful DataOps program, the tools that can help, and when to adopt a DataOps Platform.

    Speaker - Chris Bergh, Founder, CEO and Head Chef at DataKitchen
  • Graph Embeddings for Graph-Native Machine Learning Recorded: Feb 4 2021 65 mins
    Alicia Frame & Amy Hodler, Neo4j | Andy Steed, Big Data LDN
    Join us to understand how you can use graph-native machine learning in Neo4j to make break-through predictions. Previously only accessible to researchers and a very few advanced tech companies, Neo4j has democratized graph-based ML techniques that leverage deep learning and graph convolutional neural networks.

    Most data science models ignore network structure, while graphs add highly predictive features to ML models, increasing accuracy and enabling otherwise unattainable predictions based on relationships. With the recent update to the Neo4j Graph Data Science library, anyone can take advantage of this state-of-the-science technique to create representations of your graph’s most significant features for new and more accurate predictions with the data you already have.

    In this session, we’ll explain our new graph embeddings and demonstrate using the GraphSAGE embedding results with our new ML catalog. We’ll also visualize the predictions of different models using Neo4j Bloom.

    Speakers:
    • Alicia Frame, Lead Product Manager for Graph Data Science, Neo4j at Neo4j
    • Amy Hodler, Director, Neo4j Graph Analytics & AI Programs at Neo4j
  • Anatomy of real-time at Paddypower Betfair Recorded: Jan 26 2021 44 mins
    Alexandru Objelean & Rares Rusu from Paddypower Betfair & Andy Steed, Big Data LDN
    Couchbase NoSQL has started small at Paddypower Betfair. From its early beginnings, as an alternative to our classic relational databases, it has grown into a full blown system that we rely on to deliver great customer experiences. In this webinar we’ll share facts & stats from our daily operations, showing you how we got from problem to solution in a variety of use-cases: creating activity reports for our operational teams, delivering such data when the sizing reaches millions of records and operating dual datacenter clusters.
  • How SPAR Created a CPG Sales Data Exchange with Data Preparation Recorded: Jan 19 2021 51 mins
    Tom Rose, SPAR International | Dharshini Bhuvaneswari, SPAR International | Andy Steed, Big Data LDN
    SPAR is one of the world’s largest food retailers operating more than 13,000 stores in 48 countries across the globe. To understand sales trends, market conditions and the performance of different promotions, SPAR relies on data shared by their retailers and their own ability to analyze that data. You can imagine this isn’t easy!

    Comparing data across their vast network of retailers means that SPAR’s analytics team has to standardize data across different languages, currencies, formats and product hierarchies. Talk about a data wrangling challenge!

    Join this webinar to learn how SPAR utilized Trifacta’s data preparation platform to turn this massive data headache into a competitive advantage for their business. SPAR’s Head of International Operations, Tom Rose and Lead Data Analyst, Dharshini Manoharan will dig into the following topics during this webinar:

    ● How SPAR created a strategy to turn data bottlenecks into analytic opportunities
    ● What technology, people and process components were required for success
    ● Who utilizes data preparation within SPAR and where it fits in their tech stack
  • Establishing An Enterprise Data Marketplace to Shop for Data as a Service Recorded: Dec 9 2020 63 mins
    Mike Ferguson, Intelligent Business Strategies | Paul Moxon, Denodo | Andy Steed, Big Data LDN
    One of the highest priorities in organisations today is to address the issue of untrusted data which leads to inaccurate predictions, recommendations, reports and dashboards. In order to solve this, many companies are looking at creating a standard data curation process to create trusted data assets and make them available services in an enterprise data marketplace so that it is easy to find, access, share and reuse across the enterprise. This session looks at building an enterprise data marketplace, the key technologies needed and the challenges in operating one.
    • The problem of untrusted data
    • What’s needed? - Findable, accessible, reusable and trusted ready-made data assets
    • Manufacturing ready-made data assets - from data lake to enterprise data marketplace
    • What is an enterprise data marketplace? – A new role for a Data Catalog
    • What types of data and analytical assets should you expect to see in one?
    • How should an enterprise data marketplace function?
    • What is needed to operate a data marketplace in terms of people, processes and technologies?
    • Why is data virtualisation critical to serving up trusted data assets from a data marketplace
    • Maximising reuse by integrating self-service BI tools and Data Science workbenches with the marketplace
  • Eating the Elephant: A Business ROI-Driven Approach to Migrating to Cloud Recorded: Dec 8 2020 57 mins
    Steve Crosson-Smith, SDG Group | Andy Steed, Big Data LDN
    Most commentators agree that migrating legacy data infrastructure, such as data warehousing, integration and transformation, into modern cloud-based architectures will significantly benefit both business and IT stakeholders. Many projects, however, fail to secure funding because their time to value is too long or uncertain.

    This session outlines a business-centric approach to migrating to cloud-based data architectures which delivers stakeholder value 3 to 6 times faster than most alternatives, whilst significantly increasing the ability to make self-service, data-driven decisions and expand into areas such as advanced analytics. The approach itself is not tied to a specific technology stack but we will outline technologies that make this easier to achieve.
    The result is happy, enabled business stakeholders who regard IT as a business enabler, not a bottleneck.
  • Extend your SAP ECC & Oracle EBS Investment with Incorta & Spinnaker Recorded: Dec 3 2020 46 mins
    Shaun Leach, Incorta | Gary West, Incorta | Martin Biggs, Spinnaker | Andy Steed, Big Data LDN
    One of the highest priorities in organisations today is to deliver analytics business users can use. SAP upgrades can tend to be expensive and renewal maintenance can be time consuming. Join this webinar to learn about a simple way to reduce SAP annual support costs, get better response times and get insights from ECC and other data sources in days/weeks. Hear from Incorta's Senior Sales Engineer and VP of Sales, along with VP and General Manager, EMEA at Spinnaker Support.

    Moderator: Shaun Leach, Senior Sales Engineer at Incorta
    Panelist: VP of Enterprise Sales, Gary West at Incorta
    Panelist: VP and General Manager EMEA, Martin Biggs at Spinnaker Support
    and Andy Steed, Content Director, Big Data LDN
  • High Performance Cloud Data Warehouse Vendor Evaluation Recorded: Nov 17 2020 62 mins
    Pradeep Bhanot, Actian | William McKnight, GigaOm | Emma McGrattan, Actian | Andy Steed, Big Data LDN,
    This webinar brings together GigaOm analyst William McKnight and special guest, Actian’s SVP, Engineering, Emma McGrattan to discuss the intriguing results from an in-depth GigaOm Analytic Field Test derived from the industry-standard TPC Benchmark™ H (TPC-H) to compare five leading cloud data warehouse offerings: Actian Avalanche, Amazon Redshift, Azure Synapse, Snowflake, and Google BigQuery.

    Data-driven organizations rely on analytic databases to load, store, and analyze volumes of data at high-speed to derive timely insights. Data volumes within modern organization’s information ecosystems are rapidly expanding—placing significant performance demands on legacy architectures. Today, to fully harness their data to gain competitive advantage, businesses need modern, scalable architectures and high levels of performance and reliability to provide timely analytical insights. In addition, many companies are attracted to fully-managed cloud services.

    In this 1-hour webinar, you will discover:

    How cloud databases are a way for enterprises to avoid large capital expenditures, provision quickly, and provide performance at scale for advanced analytic queries
    How these leading cloud data warehouses compare on both performance and cost across a broad spectrum of real-world query use cases
    How user concurrency can materially impact both performance and cost
    Who consistently outperformed the competition in the test
  • 4th Industrial Revolution Report: Panel discussion on the 2020 findings Recorded: Nov 11 2020 61 mins
    Abhas Ricky, Cloudera | Andy Steed, Big Data LDN | James Lupton, Cynozure | Paul Maher, Positive Marketing
    The 4th Industrial Revolution Report is Independent research, commissioned by Big Data LDN that collates the opinions of 250 of the UK’s most influential data leaders. In this webinar we take a first look at this year's results and discuss their implications with members of our steering committee who helped to shape the survey.

    Report download: https://bigdataldn.com/intelligence/2020-4ir-report/

    Speakers: Abhas Ricky, VP Business & Cloud Transformation at Cloudera, Andy Steed, Content Director at Big Data LDN, James Lupton, CTO at Cynozure and Paul Maher, Founder & CEO at Positive Marketing will discuss the 2020 report.
  • Where’s the Data? Find Your Biggest Governance, Security, and Compliance Risks Recorded: Nov 3 2020 48 mins
    Sam Gillespie, OneTrust, Andy Steed, Big Data LDN
    Over the last decade, data has become the driving force behind businesses, economies, and daily life. But sometimes, something as simple as knowing what data you have, and where that data lives within (and outside of) your organization, can be your biggest governance, security and compliance risk. As stricter data laws are enacted across the globe and consumers exercise new privacy rights over their data, it’s more crucial than ever to find the best ways to find, manage, query, and action data. In this session, we’ll share tips on how to manage data in the organization, and how data discovery can help with compliance.
    • Understand how to know where data lives within and outside of your organization
    • Learn the security, governance, and compliance considerations for collecting, securing, and managing data
    • See how data discovery can help with broader data governance
  • Modernise Your Approach to Data: The Case for Cloud ELT Recorded: Oct 29 2020 57 mins
    Dave Lipowitz, Matillion, Andy Steed, Big Data LDN
    Modern businesses seeking a competitive advantage must harness their data to gain better business insights. When it comes to loading, transforming, and analysing data, the cloud changes everything. ELT is a fundamentally different approach to pre-processing data, in terms not only of architecture but philosophy as well. Today, as much data, from as many sources as possible, needs to be integrated into analyses. ELT leverages the power of the cloud and the data warehouse platform itself, to do data transformation at scale. Learn how moving from traditional ETL to cloud ELT can help you keep up with exploding data volumes, reduce coding and resource management efforts and help you become more data-driven.
  • Accelerating safe data provisioning for Analytics and Machine Learning Recorded: Oct 20 2020 66 mins
    Steve Totman, Privitar, Andy Steed, Big Data LDN, Mike Ferguson, Intelligent Business Strategies.
    How do you safely shorten time to value? The pressure is on - growing data science functions and hungry analytics teams driven by business pressure need access to an increasing number of datasets rapidly. It’s a constant balance of data’s dual status as an asset and liability. In this session we’ll explain how you can safely deliver protected data that retains analytical utility to your consumers.
  • Enterprise Data Fabric – The Key To Building A Data-Driven Enterprise Recorded: Oct 1 2020 66 mins
    Mike Ferguson, Intelligent Business Strategies | Paul Moxon, Denodo | Andy Steed, Big Data LDN
    This session looks at the emergence of Enterprise Data Fabric and its role in a modern enterprise. It firstly defines what enterprise data fabric is and why it has become strategically important in a multi-cloud hybrid computing environment. It also looks at the component capabilities that enable it and how these fit together to help connect to, simplify access, manage, govern and orchestrate the ingestion, discovery, cataloguing, cleansing, transformation, integration and analysis of data in a distributed computing environment. Finally it looks at data virtualisation and why it is a critical part of an enterprise data fabric solution

    What is enterprise data fabric?
    Why do you need it?
    What are the components of an enterprise data fabric offering and what role do these components have?
    How does Enterprise data fabric, the data catalog and AI work together?
    Why is Data virtualisation a critical capability in an enterprise data fabric solution?
    Use Cases and examples of companies who have built a data fabric using Data Virtualization

    Speakers:
    Mike Ferguson, Intelligent Business Strategies
    Paul Moxon, Denodo
    Andy Steed, Big Data LDN
  • Panel Debate: Creating and Fostering a Data-Driven Culture Recorded: Sep 10 2020 60 mins
    Zara Wells, Looker @ Google Cloud | Marco Tranquillin, Google | Alex James, Fivetran | Andy Steed, Big Data LDN
    In this panel debate 4 data leaders will be discussing the best ways to create a data driven culture. The panel will give tips on curating a Data Driven Culture, how to drive ROI and practical steps on getting started.

    Speakers:
    Zara Wells, Head of Data Culture and Transformation Programs, Looker @ Google Cloud
    Marco Tranquillin, EMEA CE Practice Lead, Data Analytics at Google
    Alex James, Sr. Director EMEA Customer Success at Fivetran
    Andy Steed, Content Director, Big Data LDN
  • Data Transformation Series: Curated, Self-Service Data with Gatwick Airport Recorded: Sep 8 2020 51 mins
    Shariq Wagener, Zsah/ Gatwick Airport | Andy Steed, Big Data LDN
    One of London’s leading airport’s Tableau journey
    Gatwick Airport struggled to create and access curated datasets at the right breadth and depth, not only for exploitation but also for reproducing management information that could easily be shared at scale. In the airport industry, spatial data is widely used to uncover new business opportunities but again the analyst community lacked the capability to meet this requirement. By deploying Tableau across the landscape, it has enabled Analysts to provision and prepare datasets for on-off and repeatable analysis for various use cases. In this session, Shariq will provide insight on the implementation journey so far and strategy for adoption that led to Tableau becoming the tool of choice.

    Speaker: Shariq Wagener, Director of Data & Analytics, Zsah/ Gatwick Airport
    Bio: Shariq is Data & Analytics Director at Zsah, starting out as an analyst he has now over 15 years of experience in strategy, execution and embedding lasting DataOps models in the transport, aviation, public sector, health, and insurance industry. With a specific focus on self-service so data can be exploited to its full potential in the right hands at the right depth, breadth, speed, truthfulness and usefulness.
  • Data Transformation Series: Working Smarter using Data Recorded: Sep 2 2020 43 mins
    Will Huntoon, Papier | Andy Steed Big Data LDN
    The Big Data LDN Data Transformation Webinar Series showcases companies who have undergone a transformative business journey fueled by data. The format usually consists of a 15-20 minute presentation from the company explaining the business context of the transformation, the need for change, barriers and how they were overcome and finally why the project was deemed successful. Following this we would have a 15-20 presentation from the software partner(s) who helped enable the journey and we’d finish with 15 mins of Q&A from the audience.

    In this webinar, titled Working Smarter using Data, we will be talking to Will Huntoon from Papier, the online gift retailer, about his Data Transformation story.

    Speakers: Will Huntoon, Papier, Andy Steed Big Data LDN
  • Returning to Work: Data-driven decisions with Tableau Recorded: Aug 20 2020 51 mins
    JP King, Tableau | Andy Steed, Big Data LDN
    As we return to work, it’s more important than ever that we make data-driven decisions to ensure the safety of our employees and are making the most of the abundance of public-facing data.
    In this demo, we’ll be using Tableau to centralise and relate multiple datasets. By associating our corporate data with public data, we can come to a wholistic view of our current situation and judge next best steps to take to so that our workforce can return to the office safely.

    Speaker: JP King, Solutions Engineer, Tableau
    Bio: JP is a Solution Engineer at Tableau based in their London office. He is responsible for helping their customers get started with Tableau so they can see and understand their data.
The UK's Largest Data & Analytics Conference and Exhibition
Our webinar broadcasts offer up-to-the-minute information and debate direct to your device on a number of different data topics.
Each webinar is a mixture of presentations, discussions, demos and industry updates designed to bring our community together, making sure we stay informed and engaged, something particularly pertinent at present.

Embed in website or blog

Successfully added emails: 0
Remove all
  • Title: How SPAR Created a CPG Sales Data Exchange with Data Preparation
  • Live at: Jan 19 2021 2:00 pm
  • Presented by: Tom Rose, SPAR International | Dharshini Bhuvaneswari, SPAR International | Andy Steed, Big Data LDN
  • From:
Your email has been sent.
or close