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Industries

Top Four Industries Using Datameer

Every industry can benefit from big data analytics whether it's increasing revenue opportunities or finding operational inefficiencies. Find out how businesses are using Datameer to increase funnel conversion, detect fraud, optimize pricing or better understand customer behavior.

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Use Cases

The Top Five Customer Use Cases for Datameer

Datameer’s big data analytics solutions can create a world of new opportunities for your business. How? By making big data analytics so simple that anyone can use it to gain insights. And we do it faster than any other solution on the market. To better understand the value of big data analytics from Datameer, we’ve captured the top five use cases that are driving the most tangible business benefits for hundreds of our customers. They’re realizing significantly greater operational efficiencies, higher revenue, lower costs, more innovative products, and more.

Customer AnalyticsCustomer Analytics

The Business Challenge

  • As a CMO, digital marketing, or customer loyalty executive responsible for optimizing customer acquisition and loyalty campaigns, you need greater visibility into the customer buying journey. Why? Because deeper, data-driven customer insights are critical to tackling challenges like improving customer conversion rates, personalizing campaigns to increase revenue, predicting and avoiding customer churn, and lowering customer acquisition costs.

    But consumers today interact with companies through lots of interaction points – mobile, social media, stores, e-commerce sites, and more – which dramatically increases the complexity and variety of data types you have to aggregate and analyze. Think Web logs, transaction and mobile data. Advertising social media and marketing automation data. Product usage and contact center interactions. CRM and mainframe data. And even publicly available demographic data.

    When all of this data is aggregated and analyzed together, it can yield insights you never had before – for example, who are your high-value customers, what motivates them to buy more, how they behave, and how and when to best reach them. Armed with these insights, you can improve customer acquisition and drive customer loyalty.

  • Increased customer conversion by 60%

    Improved targeted advertisement resulting in $1.65 million in savings

    Reduced customer acquisition cost by 30%

    Increased revenue by $20 million

Why Big Data Analytics?

  • Big data analytics is the key to unlocking the insights from your customer behavior data – structured and unstructured. It empowers you to combine, integrate and analyze all of your data at once – regardless of source, type, size, or format – to generate the insights needed to drive customer acquisition and loyalty.

    For example, imagine being able to use insights about the customer acquisition journey to design campaigns that improve conversion rates? What if you could identify points of failure along the customer acquisition path – or the behavior of customers at risk of churn so you could proactively intervene and prevent losses? How would it help if you could understand high-value customer behavior beyond profile segmentation (for example, what other companies they shop from, so you can make your advertisements even more targeted)?

Datameer Helps You Get Insights from Big Data Analytics Faster

Integrate, visualize

At Datameer, we make big data analytics so simple that anyone can turn customer data into insights – and start seeing real benefits in just 2-4 weeks. There’s no need for a technical specialist or data scientist to model, integrate, cleanse, prepare, analyze and visualize your data because your business analysts can do this themselves. We provide a one-stop-solution for getting all of your Web, advertising, mobile, social media, transaction, marketing automation, CRM and other third-party data into Hadoop; analyzing that data; and visualizing your results using wizard-led  data integration, point-and-click analytics, and drag-and-drop visualizations.

With over 55 out-of-the-box connectors to all major data sources and over 250 analytic functions – all available in a simple-to-use spreadsheet interface – Datameer empowers business analysts to easily aggregate and prepare all customer behavior data so they can:

  • Rapidly combine and enrich existing data sets with third-party, customer, and other data
  • Perform ad-hoc analytics to test what-if scenarios
  • Better understand the customer journey and identify the best campaigns that yield conversion
  • Identify the behaviors of customers at risk of churn so customer retention teams can intervene

With Datameer, you can perform customer path and market basket analysis and review decision trees to determine who and what led to the acquisition of certain products for each demographic. And you can perform interactive data discovery to identify the most common customer path and sequence of events that led to a purchase.

Learn How

New Product & Service InnovationNew Product & Service Innovation

The Business Challenge

  • Innovating new products and services – it’s the lifeblood of any business. Unless you can develop new, differentiating offerings that closely align with customer needs and desires, how else can you create new revenue streams, gain a competitive advantage and boost customer loyalty?

    Savvy companies are leveraging big data to gain insights that lead to new product and service offerings. Think CRM data, social media, transaction data, geo-location data, device, sensor and product data. You can even enrich your data with brokered, third-party data. All this and more can be used to generate insights that can lead to new products such as innovative data and analysis offerings. For example, you could sell analytics reporting to help companies make their ads campaigns more impactful. Or operationalize analytically-driven, predictive support offerings so customers can ensure 100% uptime for mission-critical servers. The possibilities are endless.

    The challenge, of course, is turning big data into insights. If you’re using traditional enterprise data warehouses (EDWs) and business intelligence (BI) software, it can take a great deal of time to collect, prepare and analyze this fragmented and often unstructured data.  And in most cases, product managers don’t know how to use business intelligence tools.

  • Media company provides brands analytic reports about consumer’s mobile interactions.

    Workday provides customers with reports on how employees use HR systems.

    Opower provides analytics reports to utility companies to help them drive energy conservation.

Why Big Data Analytics?

  • How can you bring together and analyze all of your data at once – structured and unstructured – and use it to deliver innovative new data and analytics products and services?

    Big data allows you to combine, integrate and analyze all of your data – regardless of source, type, size, or format. Now you can quickly and affordably scale to huge volumes of data and analyze them for insights (Traditional EDWs are simply too slow and costly for most companies to impact product innovation.) At the same time, you can quickly run sophisticated analytics that can’t be performed using a typical EDW – for example, clustering, click path analysis, and advanced data mining.

Datameer Helps You Get Insights from Big Data Analytics Faster

Integrate, visualize

At Datameer, we make big data analytics so simple that anyone can use it to turn big data into valuable, timely insights. There’s no need for a data scientist to model, integrate, cleanse, prepare, analyze and visualize your data. We provide a one-stop-shop for getting all your data types into Hadoop; quickly analyzing that data; and visualizing your results using wizard-based data integration, point-and-click analytics, and drag-and-drop visualizations.

Datameer gives you everything you need to monetize and analyze your big data quickly and cost effectively. We support every step in the analytics pipeline and empower you with 55 out-of-the-box connectors and pre-packaged data algorithms to jump-start the process. And features like fully customizable branding for OEMing analytics reporting, single sign-on support, and role-based security for complying with customers’ data privacy requirements allow you to offer complete solutions.

You’ve been collecting data for years – and now you can use it to grow your business and gain a competitive edge.

Learn How

Operational AnalyticsOperational Analytics

The Business Challenge

  • Manufacturing, operations, service or product executives know all too well the intense pressure to optimize asset utilization, budgets, performance and service quality. It’s essential to gaining a competitive edge and driving better business performance.

    The question is, how can you, as an IT executive, help them achieve these goals?  By quickly delivering high-impact data projects that help them achieve their goals. Armed with the right solutions, they can analyze product availability and predict product failures before they occur, optimize existing infrastructure to increase up-time, and reduce operational and capital expenditures. And they can better meet service level agreements by proactively identifying and fixing potential issues before real problems occur.

    The key is unlocking insights buried in log, sensor and machine data – insights like trends, patterns, and outliers that can improve decisions, drive better operations performance and save millions of dollars. Servers, plant machinery, customer-owned appliances, cell towers, energy grid infrastructure, and even product logs – these are all examples of assets that generate valuable data. Collecting, preparing and analyzing this fragmented (and often unstructured) data is no small task. The data volumes can double every few months, and the data itself is complex – often in hundreds of different semi-structured and unstructured formats.

  • Reduced network failure by 30%

    Decreased IT costs by 60%

    Saved $150 million annually in capital expenditures by optimizing mobile networks

Why Big Data Analytics?

  • Big data analytics is the answer. It’s so powerful because it enables you to combine, integrate and analyze all of your data – regardless of source, type, size, or format. For example, you can quickly grab structured data such as CRM, ERP, mainframe, geo location and public data and combine them with unstructured data such as network elements, machine logs, and server and web logs. And then, using the right analytical tools, you can use this data to detect outliers; run time series and root cause analyses; and parse, transform and visualize insights from your data.

    For example, you can use customer and device usage across networks to identify high-value usage. Or correlate operational, usage and cost data across operations to identify low-value segments. You can integrate and analyze historic machine data and failure patterns to predict and improve mean time-to-failure – or ERP purchase data and supplier data to optimize supply chain operations. And you can use sensor and machine data to identify and resolve network bottlenecks. The possibilities are endless.

Datameer Makes Getting Insights from Big Data Simple and Fast

Integrate, visualize

At Datameer, we make big data analytics so simple that anyone can use it to turn log, sensor and device data into valuable, timely insights. And we can do it faster than any other solution on the market.

Using Datameer, you can ingest, cleanse, prepare, analyze and visualize all of your data in hours or days, not months. We provide a one-stop-shop for getting all of your sensor, log, and other machine data into Hadoop; quickly analyzing that data; and visualizing your results using wizard-based data integration, point-and-click analytics, and drag-and-drop visualizations.

With over 55 out-of-the-box connectors to all major data sources and over 250 analytics functions – all available in a simple-to-use spreadsheet interface – Datameer empowers IT and business analysts to quickly and easily turn big data into insights. They can integrate disparate data types without pre-modeling data, scale economically by storing and analyzing every event using Hadoop, analyze and view data without IT involvement, uncover hidden patterns and correlations using data discovery tools, use visual data profiling to visually detect anomalies in data, and more.

Companies in telecommunications, high tech, and financial services – as well as those engaged in leveraging the “internet of things” – are using Datameer to get amazing results. In just 2-4 weeks, our customers have gained insights that helped them:

  • Reduce network failure by 30%
  • Decrease IT costs by 60%
  • Save $150 million annually in capital expenditures by optimizing mobile networks
Learn How

Fraud & ComplianceFraud and Compliance

The Business Challenge

  • If you are responsible for security, fraud prevention, or compliance, then data is your best friend – if you can use it to identify and address issues before they become problems. The fact is, security landscapes and compliance requirements are constantly evolving, as are the methods that the bad guys are using to defraud your business and customers.

    Data-driven insights can help you uncover what’s hidden and suspicious – and in time to mitigate risks. For example, analyzing data can help you reduce the operational costs of fraud investigation, anticipate and prevent fraud, streamline regulatory reporting and compliance (for instance, for HIPPA), identify and stop rogue traders, and protect your brand.

    But this requires aggregating and analyzing data from a myriad of sources and types and analyzing it all at once – no small task. Think financial transaction data, geo-location data from mobile devices, merchant data, and authorization and submission data. Throw in data from lots of social media channels and your mainframe data, and you have a significant challenge on your hands.

    But with the right tools, this melting pot of data can yield insights and answers you never had before – insights you can use to dramatically improve security, fraud prevention, and compliance.

  • Identified and prevented $2 billion in potential credit card fraud

    Avoided $5.5 million in data breach costs

    Lowered the OpEx and CapEx associated with fraud detection and prevention

Why Big Data Analytics?

  • Big data analytics is the key to turning your data into insights, as it enables you to analyze all of your data together – both structured and unstructured. It’s so powerful because it enables you to combine, integrate and analyze all of your data at once – regardless of source, type, size, or format – to generate the insights and metrics needed to address fraud and compliance-related challenges.

    For example, you can perform time series analysis, data profiling and accuracy calculations, data standardization, root cause analysis, breach detection, and fraud scoring. You can also run identity verifications, risk profiles, and data visualizations and perform master data management.

Datameer Helps You Get Insights from Big Data Analytics Faster

Integrate, visualize

At Datameer, we make big data analytics so simple that anyone can use it to turn their data into insights that simply weren’t never possible before. There’s no need for a technical specialist or data scientist to model, integrate, cleanse, prepare, analyze and visualize your data. We provide a one-stop-solution for getting all of your transaction, geo location, merchant, authorization, social media and mainframe data into Hadoop; quickly analyzing it; and visualizing your results using wizard-based data integration, point-and-click analytics, and drag-and-drop visualizations.

With over 55 out-of-the-box connectors to all major data sources and over 250 analytic functions – all available in a simple-to-use spreadsheet interface – Datameer empowers business and compliance analysts to rapidly integrate many different source of data and analyze it. For example, they can quickly iterate through fraud pattern changes, perform time-series analytics, detect anomalies using strong data profiling, and more.

At every step, they can take advantage of strong metadata management and data lineage functions, machine learning capabilities, intuitive self-service, and data profiling (for example, to detect anomalies in data that could lead to fraud detection and identification of compliance violations). You can also perform Smart Sampling, which enables interactive analytic data discovery and design.

Our solutions delivers bottom-line results. For example, in just 2-4 weeks, Datameer customers have gained insights that helped them:

  • Identify and prevent $2 billion in potential credit card fraud
  • Avoid $5.5 million in data breach costs
  • Lower the OpEx and CapEx associated with fraud detection and prevention

EDW OptimizationEDW Optimization

The Business Challenge

  • Enterprise data warehouses (EDW) are critical business and IT resources today – but as the size and complexity of the data to be analyzed increases, you’ll eventually hit the limits of traditional data warehouses. You’ll know it when your processing times take too long to meet business needs, your costs get out of control, or you struggle to process and analyze new data types. For both IT executives and key stakeholders responsible for analytics, business intelligence and enterprise data, this is a serious problem. Today’s business decision makers simply can’t afford delays in insights anymore.

    The solution is to offload the most challenging data management and analytics activities to new technologies and management approaches designed to handle them. For example, do you need to cut the costs of data preparation and cleansing? Reduce time to insight by offloading the most time-consuming analytical tasks? Support a variety of new data types, especially unstructured data? Or better manage rapidly growing log, sensor and other unstructured data?

    The good news is, big data analytics solutions that run on Hadoop can solve these challenges.

Why Big Data Analytics?

Big data analytics solutions running on Hadoop make it easy to overcome these challenges because they allow you to cost effectively scale to any volume of data and store and analyze any and all data types together – both structured and unstructured. You can also use them to extract structured data from your EDW into Hadoop for cheaper storage and then send back into EDW for analytics. All data can be analyzed as is, eliminating costly data preparation activities.

At the same time, big data analytics is so powerful because it enables you to combine, integrate and quickly analyze all of your data at once – regardless of source, type, size, or format – to generate the insights your business needs. In addition, you can parse, clean, profile, match, enrich, aggregate, and normalize data, as well as manage ETL workloads and generate master data. Below are the top three use cases of using Hadoop for EDW optimization:

  • Use Case #1

    Move all data to Hadoop for analysis and storage (re-platform)

  • Use Case #2

    Migrate expensive data preparation & analytics to a lower cost environment

  • Use Case #3

    Use Hadoop to deal with variety of data types

Datameer Helps You Get Insights from Big Data Analytics Faster

At Datameer, we make big data aggregation, management and analytics so simple that anyone can use it to turn their data into insights never even possible before. There’s no need for a technical specialist or data scientist to model, integrate, cleanse, prepare, analyze and visualize your data. We provide a one-stop-solution for getting all of your transaction, geo location, merchant, authorization, social media and mainframe data into Hadoop; quickly analyze it; and visualize your results using wizard-based data integration, point-and-click analytics, and drag-and-drop visualizations.

With over 55 out-of-the-box connectors to all major data sources and over 250 analytic functions – all available in a simple-to-use spreadsheet interface – Datameer empowers business analysts to rapidly integrate many different sources of data and analyze it. Our solution supports transaction, interaction, and observations data and enables seamless, bi-directional integration between all major EDWs, such as Oracle, Teradata, and Netezza. In addition, it supports self-service data extraction, preparation, and cleansing by business analysts and enables exploratory or ad-hoc data discovery.

Using Datameer and Hadoop at every step, you can take advantage of linear scalability, point-and-click data preparation and cleansing, visual data profiling functions, and a metadata repository that automatically tracks data lineage. You also get strong security, monitoring and scheduling capabilities and a schema-on-write approach that eliminates the need to pre-model data.

Together, these capabilities provide a cost-effective, linearly scalable and flexible solution that drives the fastest time to insight when compared to all other solutions.

Big Data Use Cases: Financial Services Financial Services

 

Leading financial service organizations are using big data analytics for both compliance and regulation, as well as building the business by getting advanced insights into customers, markets and operations.

Customer Segmentation

Discover how big data analytics can help correlate customer purchase history and social media data to better understand who the customers are and what they care about so marketers can better target promotions.

Read more

Fraud Detection

Credit card fraud has become increasingly sophisticated and fraudsters are using disparate databases to their advantage. With Datameer, business users can pull all different data sets into Hadoop, which helped this financial customer identify more than $2B in fraud.

Read more

Big Data Use Cases: Gaming Gaming

 

In the competitive world of online games, every click and every interaction creates incredibly valuable data that, if aggregated and analyzed, holds the answer to keeping players engaged and coming back for more.

Behavioral Analytics

The game for gaming companies is to increase customer acquisition, retention and monetization. This means getting more users to play, play more often and longer, and pay. First, analysts use Datameer to identify common characteristics of users. As a result, gaming companies can target these users better with the right advertising placement and content. To increase retention, analysts use Datameer to understand what gets a user to play longer. A user who plays longer and interacts with other players makes the overall gaming experience better. To increase monetization, analysts use Datameer to identify the group of users most likely to pay based on common characteristics. As a result of this analysis the company was able to double their revenue to over $100M.

Behavioral Analytics

Variety
Game event logs, user profile data, social interaction data captured during games between players

Volume & Velocity
150+ points of data collected from millions of monthly users

Big Data Use Cases: Retail Retail

 

As the retail industry evolves and online marketplaces continue to grow, learn how leading retailers and e-tailers are using big data analytics to increase customer engagement while reducing IT spend.

Market Basket Analysis and Pricing Optimization

Retailers and e-tailers have more data available to them than ever before. From historical transactions, to current inventory, pricing, and more, the value in these datasets increase exponentially when combined. Find out how this leading retailer used Datameer to combine datasets to come up with competitive pricing, determine where to target ads, and more.

Read more

High Tech High Tech

 

With new data sources from hardware, software and applications cropping up each day, there are countless practical applications of big data analytics to increase revenue or decrease costs in the high-tech sector.

Optimize Funnel Conversion

Tracking a lead all the way from AdWord click through to transaction requires that several database silos be broken down, and disparate datasets be joined. Learn how Datameer helped one company earn $20M in additional revenue by optimizing funnel conversion.

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Predictive Support

Machine-generated data holds a lot of valuable information when it comes to tracking system health, which, if aggregated and analyzed, can mean millions in savings. Learn how this company used predictive support to reduce their number of network failures by 30%.

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Predict Security Threats

The average cost of a data breach is $5.5M. See how this company used Datameer to track a virus across geographies and ultimately predict where the next threat would occur, reducing the risk for a potential data breach.

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Device Analytics

At enterprise hardware companies, allowing business users to aggregate and analyze structured and unstructured data generated from various devices means multiple departments from support, to marketing, sales and development can all benefit from valuable insights.

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