Big Data & Analytıcs
Big Datachanges the world dramatically. Organizations are assessing how should they analyze the data and should take actions based on that. Ereteam offers best-of-breed technologies and best practices on the space of big data. Together with our proven practices and best-in-class technologies IT and Business Users don’t need to learn any coding or complex algorithms for analyzing big data. Our Self-Service tools are providing best time-to-market value to organizations for achieving maximum productivity.Ereteam focuses on visual analytics to solve the most complex big data problems.
Common use applications include:
- Customer Analytics: Unlocking customer 360 insights and digital marketing campaign intelligence
- Cybersecurity: Detecting and preventing cybersecurity threats and attacks
- Risk Mitigation: Risk Mitigation: Iterating financial risk models and designing data visualizations to provide transparency and auditability for regulatory compliance and trade surveillance
- Internet of Things: Internet of Things: Turning IoT and sensor data from millions of devices into meaningful lifecycle analytics
- Data Lakes: Data Lakes
Customer Analytıcs & Rısk Management
Analyze large volumes of multi-structured data for insightful product development and engage customers with web-based interactive visual applications. Leverage alternative data for trading strategies with an edge.
Model and Manage Stress Tests
Evaluate how entities perform against a series of adverse market scenarios. You can imagine in the background, algorithms testing different ways to free up liquidity. Those changes could be reflected here. When you see a graph you like, you can package that data and use it as part of a management plan provided to auditors.
Prove a robust and defensible process by validating risk models in granular detail by correlating machine, historical, and real-time data; inclusive of chat, voice, emails, trade execution, and post-trade events.
Deep forensics for monitoring trade activity in real time is a complex big data problem for most large businesses. Our visual analytics software enables the identification of abusive trade behavior (the “needle”) within the mass of electronic communications and high velocity, cross-jurisdictional trade volume (the “haystack”) in real time.
Out-of-the-box Cybersecurity Visualization
Providing out-of-the-box cybersecurity visual analytics across diverse and ever-growing digital endpoints, information networks, and user information. This enables analysts to quickly identify cyber threats, effectively perform forensic analysis, and hunt for the unknown.
Drill across endpoint, user, and network with real-time dashboards to identify critical metrics. Easily embed results into case management tools for effective resolution.
Agile Detection, Investigation, Response
Cybersecurity threats are dynamic events perpetrated for any reason by any internal or external party, using both physical and cyber points of entry. We integrate directly with machine learning to accelerate threat detection and response.
Optimize forensic analysis with visuals that make time-series analysis simpler and fast filtering across a well known set of attributes. Understand relationships with graph visualization.
Internet of Thıngs
- Collect and analyze data from vehicles, in-road sensors and other sources in a single platform.
- Visually analyze real-time streaming telematics data alongside historical data for deeper pattern analysis.
- Understand traffic patterns, offer more targeted insurance packages and provide specific service recommendations.
- Remotely diagnose fleet issues.
- Ingest real-time and batch data from all sensors and components.
- Visually analyze historical patterns within massive data sets to predict which components and pieces of equipment are likely to fail.
- Avoid costly downtime by repairing parts proactively.
System Log Analysis
- Collect, store and analyze all logs in a single platform.
- Efficiently diagnose and solve system issues remotely.
- Analyze how various features, components and configurations affect system performance.
Data Center Monitoring
Turn IoT data from enterprise data servers into meaningful lifecycle analytics. Understand which components are failing, compare components across vendors, learn which features are being adopted and identify servers that are near capacity.
You can Get More Insights From Your Data Lake
BI & Analytics
It lets you design data-native, visual analytic applications directly on your data lake. Your users can access these apps from their web browser for advanced business intelligence and analytic insights.
Your customer data is now in your data lake. Unleash the power of that data for your marketers, product managers and sales teams through it , so they can improve your products, services and operations by understanding how your company interacts with customers across all channels.
Clickstream / Journey Analysis
Web data often is the primary data source to begin building data lakes. Together with our tool and expertise we can provide advanced path and flow diagrams so your web and marketing teams can better understand how customers traverse and interact with your digital properties.
BI & Vısualızatıon
The New Promise of BI for Data Driven Organizations - All decision makers can access data and use it effectively, from casual to power users.
Data is most critical and valuable assets for the organizations. We need to analyze data to know our customers, to improve the quality of our products and services, to develop the our people talents and finally to increase the revenue and profit of our organizations.
Ereteam helps companies with proven industry experiences and best-in-class BI tools to address their data visualization and analysis needs. The capabilities and features of modern BI tools and technologies are now allow people to see and understand their data in a best easiest way. Ereteam partners with world most successful software vendors in BI space.
Ereteam meets all the BI needs small and big organizations in every level of business users, for CxOs, Business Analysts, IT Users and all others. Typical BI project areas are as follows:
- Dashboards & Visualizations
- KPI & Scorecards
- Data Discovery
- Mobile BI
- Ad-hoc Reporting
- Formatted and Advanced Reporting
- Search based BI
- Artificial Intelligence in BI
- Operational BI
Gartner provides research and analysis about BI & Analytics Platform markets. Below are the Critical Capabilities for Business Intelligence and Analytics Platforms published by Gartner.
Admin, Security and Architecture:
Capabilities that enable platform security, administering users, usage monitoring, auditing platform access and utilization, optimizing performance and ensuring high availability and disaster recovery. This also includes the ability to run on multiple operating systems.
Data Source Connectivity:
Capabilities that allow users to connect to structured and unstructured data contained within various types of storage platforms, including personal data sources, relational, NoSQL and direct HDFS. The ability to access business applications and ERP systems is included.
PaaS and SaaS for building, deploying and managing analytics and analytic applications in the cloud based on data both in the cloud and with hybrid connectivity to on-premises data sources. Marketplaces and prebuilt content to cloud-data sources are included.
Self-Contained ETL and Data Storage:
Platform capabilities for accessing, integrating, transforming and loading data into a self-contained performance engine with the ability to index data and manage data loads and refresh scheduling of loaded data.
Self-Service Data Preparation:
Drag-and-drop cleansing, modeling, and blending of multiple data sources and creation of analytic models. Advanced capabilities include machine-learning-enabled semantic autodiscovery, intelligent joins, intelligent profiling, hierarchy generation, data lineage and data blending on varied data sources, including multistructured data.
Tools for enabling users to leverage the same system-of-record semantic model or for creating a semantic model automatically. Modelers should be able to search, capture, store, reuse and publish metadata objects such as dimensions, hierarchies and measures, as well as conduct impact analysis for changed objects.
Embedded Advanced Analytics:
Enables users to easily access advanced analytics capabilities that are self-contained within the platform itself, or through the import and integration of externally developed models.
Smart Data Discovery:
Automatically visualizes the most important findings such as correlations, exceptions, clusters, links and predictions in data that are relevant to users without requiring them to build models or write algorithms. Users explore data via visualizations, autogenerated voice or text narration, search, and natural-language query technologies. Forecasting and clustering should be menu-driven. Support for advanced visualizations such as decision trees should be out-of-the-box.
Interactive Visual Exploration:
Enables the exploration of data via an array of visualization options that go beyond those of basic pie, bar and line charts, to include trellis, heat and tree maps, scatter plots, and other special-purpose visuals. These tools enable users to analyze and manipulate the data by interacting directly with a visual representation of it to display as percentages bins and groups.
The ability to create highly interactive dashboards and content with visual exploration and embedded advanced and geospatial analytics to be consumed by others. Support for offline dashboards should be included.
Mobile Exploration and Authoring:
Enables organizations to develop and deliver content to mobile devices in a publishing and/or interactive mode. Takes advantage of the native capabilities of mobile devices, such as touchscreen, camera and location awareness. Device-based security and integration with third-party MDM solutions should be supported.
Embed Analytic Content:
Capabilities including a software developer's kit with APIs and support for open standards for creating and modifying analytic content and visualizations, and embedding them into a business process, and/or an application or portal.
Publish, Share and Collaborate:
Capabilities that allow users to publish, deploy and operationalize analytic content through various output types and distribution methods with support for content search, scheduling and alerts. Enables users to share and rate content via discussion threads, chat and storyboards.
Platform and Workflow Integration:
This capability considers the degree that the capabilities are offered in a single, seamless product or across multiple products with little integration.
Ease of Use and Visual Appeal:
Ease of use to administer and deploy the platform, create content, consume and interact with content as well as the visual appeal.
Customer Engagement Solutıons
Customers want relevant, personalized and consistent interactions. Catalysts such as social media, real-time access to information and mobile devices are redefining what they expect. These trends are fundamentally changing how marketing must work to improve business success.
Customer Data Management
- Customer Data Integration
- Customer Data Quality
- Single View of Customer
Omni-Channel Campaign Management
Managing large-scale, multi-wave, and multi-channel campaigns
Select and segment a target audiences that can be used across campaigns at scale. Assign offers to individual segments and suppress or test with others. Track responses and performance of campaigns for further retargeting.
Central repository for reusable offers, segments, and contact & response history
Not only does Campaign Management execute campaigns, it also creates a central repository for re-usable offers, segments, and contact response history, so marketers don’t need to reinvent the wheel for each campaign.
Offers created based on templates with standard and custom attributes can be dynamically generated for each campaign target - allowing you to easily manage complex campaigns
Provide the best customer contact experience, basing engagements on the interaction history, offer details, channel preferences, time frame, business constraints and rules and marketing objectives.
Minimize customer contact fatigue by mathematically determining the best communication for each customer
Marketıng Plannıng and Operatıons
Gain better control over their budgets and processes, align resources to objectives, streamline production processes, track budgets and expenses, and improve team collaboration.
Campaign project tracking, accountability, strategic program collaboration and asset management across the entire company in addition to outside agencies
Real Tıme Personalızatıon
Determines, in real-time, best message for each interaction
Instantly determines the best personalized message to present to each customer during a live interaction through all inbound channels.
A combination of segmentation logic, marketing rules and algorithms monitor interactions over time and automate the process of building personalization models
Plug into any customer touch point
Present personalized offers to customers – wherever they choose to contact you. From websites to kiosks, from call centers to mobile apps, IBM’s real-time capabilities are channel-agnostic.
Behavior can be understood across channels and effect decisions anywhere
Personalizes based on historical data and new data from each interaction
Make personalization decisions based on both historical data and new information gathered during a current interactions.
Constantly learning, gaining valuable decision-making information over time to present the most personalized offers
You can create a single customer identity and deliver a consistent, personalized customer experience across channels—email, mobile, web and social—for higher online conversion rates and increased order value.
Easily create and edit highly relevant email content.
Effectively engage with your always on-the-go audience. Capture mobile insights in real time and drive personalized mobile experiences to each contact through email, SMS, simple/rich push notifications and connected devices like the Apple Watch.
Design and automate consistent cross-channel experiences using a visual planning tool that allows you to collaborate across the marketing disciplines; gain quick consensus with colleagues.
Customer Engagement Analytıcs
Visualize the customer journey
Visualize complete, cross-channel customer journeys across devices and over time. Know where customers are in their journey and learn how activity in one channel impacts performance in another.
Gain the insights you need
Bring together customer experience insights from multiple channels in a unified dashboard. Identify trends and understand root causes. Get immediate insight to go from question to decision in minutes.
Re-live customer experiences
See where customers struggled and pinpoint trouble spots. Replay sessions to see what your customer experienced. Identify opportunities to improve the customer experience and refine the journey.
- Customer Data Integration
- Customer Data Quality
- Single View of Customer
Ereteam is helping to organizations to manage their most important assets: DATA
Below are the major areas of data management functions of an organization:
A fast and cost effective process of combining data from many different sources into an application. You need to deliver the right data in the right format at the right timeframe to fuel great analytics and business processes.
Self Service Data Preparation
Prep, blend and analyze all relevant data needed to answer a faster business question.
Access all your relevant data
Connect to and cleanse data from data warehouses, cloud applications, spreadsheets and other sources
Prep and blend the right data
Create the right dataset for analysis or visualization using data quality, integration, and transformation tools
Make the most of spatial or location data
Blend and output spatial data files then easily join it with 3rd party data such as demographics
Get data ready for predictive analytics
Accelerate the processes of creating predictive analytics with specifically designed tools
Master data management
Manage, govern and share your data assets.
Operational Data Management
Business team and system collaboration depends on accurate data assets. Creating, governing and distributing that operational data—customers, products, suppliers, reference data
Data Management for BI & Big Data
Accurate BI and reporting require conformed enterprise dimensions, attributes and hierarchies. Business intelligence and big data teams govern their analytical reference data
Financıal Performance Management
Improving the Organizational Performance with Integrated Planning and Go Beyond The Finance
Enterprise Planning can go beyond the finance with the collaboration between departments, there is a great value to link operational and financial planning.
CFOs expects below bullet points from a Planning Tool/Application:
- Functional Capabilities
- Ease of Use
- Reporting Capabilities
- Modeling and Analytical Capabilities
- Quick and Inexpensive Implementations
- Compatibility with Excel
- Total Cost of Ownership
Ereteam offers extensive capabilities with the combination of technology and solution expertise in Enterprise Planning and Performance Management Projects.
Ereteam addresses all the planning needs at the office of CFO and CxOs. Below are the typical pain points or challenges organizations faces.
Best Practice Financial Reports
We understand what you are looking for in a financial reporting environment. We are offering "finance owned" reporting solution with highly flexible Excel-like functionality and "financially intelligent" Best Practice Financial Reports.
FINANCIAL REPORTING TEMPLATES
Together with 14 highly flexible Best Practice Financial Reporting templates and one custom free format template, with which you can create your own flexible output from scratch by dragging and dropping a whole set of different reporting components onto an empty grid.
HOME PAGE TEMPLATE
Many of our customers use this template as the starting point when opening up the Financial Reporting Applications. It is specially designed to give the end-user an immediate view of the performance of the company by showing the most important KPIs in the middle of the screen as well as specified news items.
MULTIPLE SCENARIO ANALYSIS
With this template you can combine several scenario-trends in one axis-frame. For example, it is possible to show the Actuals until the current period and the Forecast for the rest of the year.
MULTI COLUMN REPORTS
The Multi-Column template is suitable for creating a dashboard with a flexible number of columns and rows. It is an easy and flexible way of building a report that will look exactly the way you want it to look. It includes rows and columns customizing features, drill down capability and automatic variance coloring.
With reports based on this template you will be able to see the trend in the two categories and see which analytical dimension member and entity is causing this difference. This template is often used for P&L, balance sheet, and cash flow reports. The variance column will give you an indication of accounts that need attention.
This template is used for reports that give insight into the build-up of an account (or any other dimension) typically for non-financial users of the application. The example on the side shows how the different underlying accounts add up to Return on Assets. If you click on an underlined member, you will be automatically redirected to a report with more detail.
The waterfall or cascade graph is a very popular graph, used to analyze the difference between actual and budget (or any other reference category) or to analyze movements from last year to actual date. By selecting a line, the right top pane shows the trend of that specific member. Alternatively, you can drill down in the member structure. You can filter the value tree through another dimension and the view automatically zooms to the relevant part.
This best practice report was created after a request from the user community that wanted to analyze two related accounts in one graph. Typically this graph is used to analyze Receivables and Days Receivable, or Price and Volume. In the right top pane, the numbers are broken down into the underlying Entities. Clicking on these Entities, gives the user the ability to analyze the numbers broken down into their underlying Entities.
The ratio analysis is often used to detect odd movements in certain Revenues or Costs. By analyzing Cost types as a percentage of the Total Costs or Total Revenues, high volatility in the graph highlights any strange movement in the Costs. By switching to the absolute values, users can quickly analyze if the movement is a notable event. Drilling down to lower level Entities gives users even more flexibility to analyze the numbers.
MULTIPLE BAR & LINE CHARTS
This is the ideal template to show trends for different accounts (and/or members from other dimensions). You can mix line-charts and bar-charts and you can display up to 6 axis-frames in one report.
This best practice report is perfect for benchmark one or more peer groups on an account or any particular KPI derived from the underlying EPM system. This can be particular useful for HQ facilities, given that the tight security of HFM usually restricts access to this type of underlying data. For benchmark purposes within our application this type of data can be drawn out of HFM or Hyperion Enterprise.
This template is used to analyze the different components of an account. With these reports you are able to analyze the composition of an account. You can also see the trend per component for two categories. Another example how to use this template is a report for analyzing cost structure trends. You will be able to see the development of total costs as well as the contribution of the individual components.
This template helps analyze the relation between three accounts within an analytical or entity dimension.
This Ranking dashboard gives you a quick overview of the best and worse performers, based on a selected list of Accounts defined for your organization. The ranking can be done on absolute values (of Actuals or another Reference Category) or on the better/worse Variance or Variance%. By showing both the top and bottom performers, you instantly see the Entities/Products/Markets etc. that require specific attention.
FREE FORMAT TEMPLATE
In addition to the set of 13 pre-configured templates, there is also the possibility to create your own Free Format templates. While the pre-configured templates help our customers save significant amounts of time and effort on standard reporting scenarios, they clearly also have many highly specific requirements. The highly flexible free format templates give you the freedom to built any type of output or report you desire.
Retail Pricing Optimization
Industries First OmniChannel pricing solution for global retailers
We allow pricing professionals at all levels within a retail organization to witness the ease available in setting pricing strategy and reviewing and manipulating prices – afforded by current pricing technologies from ereteam.
- Create pricing rules across zones, online and in-store
- Run what-if scenarios on category-level strategies
- Output prices to price review screens with complete transparency to prices
- Run interactive merchandise analytics over the data
Play by the Rules: how should optimization systems solve, report and manage pricing rules?
Retail pricing rules are more important today than ever to enforce a retailer’s price strategy, compete effectively and deliver a consistent shopping experience. How rules are handled inside optimization solutions is critical. Optimization cannot be solved 1st and rules solved 2nd – as it has been done for years – otherwise rules violations will proliferate; pricing inconsistencies will occur and same-store sales will erode.
Big Data Converges with OmniChannel Retailing for Competitive advantage
Big data is a game-changer because of its connection to OmniChannel retailing. Today, OmniChannel shoppers use catalogs, blogs, review websites, comparison shopping engines and then shop in-store, at kiosks, on your website, and use multiple devices including computers, tablets and smart phones – often within the same shopping transaction. This interaction of devices and channels has expanded the customer data available and data management challenge and yet holds the key to creating an interconnected shopping experience which drives loyalty and sales.
Markdown Optimization Demands a Seasonal Facelift – Omni-Style.
What has changed is the need for an OmniChannel pricing architecture that rationalized prices online and in-store, dynamically neutralizes Amazon’s competitive incursions, and provides more flexibility and scalability for increasingly localized and granular markdown budgets and programs. We propose that the new toolset for Markdown Pricing includes lifecycle demand modeling, and OmniChannel rules engine, competitive price surveillance, integrated budgeting and strategy, constrained optimization , and merchandise analytics and reporting. The focus of this paper is to elevate the primary considerations for markdown pricing strategy en route to competing more effectively.
Competitive Pricing in OmniChannel Retail. What are you missing?
Mobile and online technologies have changed the competitive landscape by providing consumers broader assortment choices with increased price transparency. This disruption has altered the basis of competition in favor of assortment and price and prompted in some cases indiscriminate price matching. A competitive response is imperative, but with whom, where and on which products? In other words, we need to rethink how we compete on price and assortment in a changed retail economy. In this paper we explore the pitfalls of price matching and introduce new important merchandising questions for competing effectively in OmniChannel retail.
Managing Consumer Demand and Competition across Channels
Online transparency (price & product) enabled by online/mobile technology has created an “always-on” shopping experience for consumers which has altered the basis of competition in retail. Retailers today require an integrated approach for assortment, price & promotions across channels, which is more “demand-driven”, responsive to competition and takes a single view of the OmniChannel enterprise. OmniChannel Demand Management (ODM) is a new category of solutions which answers the needs for this evolving retail supply chain so consumers enjoy a seamless shopping experience and retailers compete effectively.
Exercising Retail Price Leadership
The popularity of price matching jumped 187.5% during the 2014 holiday sales season. If this trend continues, how will retailers compete effectively and maintain profitability? Recent technology advances allow retailers to differentiate themselves, build customer loyalty and exercise price leadership – not simply adopt a “follower” strategy. In this paper we investigate omnichannel retail pricing practices, redefine important industry concepts and affirm retailers that price leadership is possible.
Customer Journey Analytics
Accepts data from ANY data source where there is an event name and timestamp by easily ingesting data from your existing, native, data repositories.
Amazing opportunities lie hidden in your data that are only uncovered when events are connected into journeys. The user interface enables business users and data experts to apply years of experience through a proprietary journey language.
Business users sequence ANY & ALL interaction events and categorize them from the customer point of view, enabling robust journey management.
Rapid Journey Analytics
Visually explore and analyze connected journeys, while making contextualized journey data available to downstream systems and projects. With data automatically and continuously collected, connected and contextualized, you can focus on what's important.
Unlock Your SAP Data
Integration of SAP ERP and BW
The Xtract Universal Component Suite offers nine components to provide all kinds of SAP interface
technologies, such as Tables, Queries, BAPIs, ABAP Reports or Hierarchies. Besides that a Delta-Mechanism is also available and forms the top class of the BI components for SAP-Tableau/Qlik/Microsoft-Integration.
ERPConnect - Get connected to SAP
ERPConnect offers a .NET API for all kinds of SAP objects to enable easy interface implementation and design for developers (e.g. function modules, SAP queries, IDocs, RFC server, BW Cubes etc.).
Xtract IS - Plug'n'Play for SAP and SQL Server Integration Services
Integrate all kinds of SAP and BW data into your SSIS-based ETL process. The Xtract IS Suite offers nine different components to implement your data flows.
Xtract RS - SAP Reporting with MS Reporting Services
Use Microsoft Reporting Services to create and publish powerful reports based on your SAP data without any additional staging layers. The Xtract RS data provider gives you access to SAP tables, queries, BAPIs and BW Cubes.
ERPConnect Services - Connect Microsoft SharePoint and SAP
ERPConnect Services consists of three components for seamless, straightforward integration of SharePoint and your SAP ERP / BW system. It does not require any additional middleware – the integration takes place entirely within the SharePoint stack.
Xtract PPV - Connect PowerPivot with SAP
Connect all kinds of SAP Businessdata in Microsoft PowerPivot. Xtract for PowerPivot gives you access to SAP tables, Queries, BAPIs and RFC as well as BW Cubes and ABAP Reports.
Xtract Universal - Automatic Data Warehousing
Integrate your SAP data in the most different target systems - fast, straight-forward and user-friendly.
Data Governance For GDPR Compliance
Assess. Prepare. Comply.
Our GDPR Solution does the heavy lifting so you don't have to. We provide the experts, the formula, the methodology and the assets you need to successfully comply with the new regulation. We'll help you create transparent and demonstrable best practices and put those to work - defining what data can be classified as GDPR personal information; discovering where this data lives, who uses it and how is it used; connecting that information to data governance processes; enabling collaboration with all stakeholders across the organization; and supporting engagement with regulators.
Reduce Compliance Risk & Fines
Penalties for non-compliance can be as high as 4% of gross revenues. Ensure that you are not subjecting your organization to fines or additional risk.
Align Capabilities to Support Compliance
Link GDPR-related processes, rules, standards, data and metrics to your organization's compliance goals and objectives.
Build Trust with Stakeholders
Demonstrate to customers that personal information is handled appropriately and that you can verify partners' compliance with GDPR.
Self Service Data Preparition
Actionable information for everyone
Today, the biggest challenge enterprises face is simply getting the data ready for analytics and decision making. Bringing together multi-structured data from diverse sources, preparing data, and combining additional data to provide more context are just a few challenging tasks that continue to confront modern enterprises. And, the modern enterprise requires an Adaptive Information Platform.
Our tools and technologies are built to satisfy those who want to dramatically increase their productivity of ever-increasing data volumes while reducing the trap of data chaos. Business analysts work within an intuitive, visual, self-service data preparation application to gather, prepare and publish data with clicks, not code, with complete governance and security. IT teams administer the scale of data volume and variety, data sources, and business scenarios for both ad-hoc and repeatable data service needs.
As greater volumes and types of data become necessary for analysts to enable critical decisions, blending data sources to gather insights is now more important than ever. Unfortunately, many data analysts try to accomplish this using Microsoft Excel or other tools that were not designed for preparing and joining the influx of new data. Frustrated, they turn to their IT department or data scientists within their organization to write code and manually build the analytic dataset they need, losing precious time and control.
We eliminate this frustration through self-service data analytics that allows line-of-business analysts themselves to access, cleanse, and blend data from multiple sources using drag-and-drop tools with no coding required. This enables the people who know the data the best to easily create the actionable analytic dataset they need for business decision making (such as retail site selection, or multichannel profiling), or for driving a specific business process (such as packaging data for sale by data aggregators.Key capabilities for Data Blending:
- Connect to and cleanse data from data warehouses, cloud applications, spreadsheets and other sources
- Easily join data from multiple sources to deliver a more complete dataset
- Repeatable workflow design that provides insight into every step of the data blending process, and allows you to automate future projects to save time and eliminate errors