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Breaking Through The Data Bottleneck: A Customer Case Study In Agile ETL

As a sequel to our webinar, “Breaking Through Your Data Bottleneck With Agile ETL”,  we’ll be interviewing our customer, FairPoint Communications on the challenges faced while making the transition from traditional ETL processes to Lavastorm Agile ETL. Fairpoint will specifically address how this approach accelerated projects without compromising governance, quality and accuracy.

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Vendor Landscape – Data Preparation Tools

Analysts and consumers of data both spend significant amounts of time wrangling data in order to conduct analyses and gain insights. The data in their systems lacks the context of their questions, decisions, or business actions. Enterprise architects take note: New big data environments, faster data integration, and analytic appliances aren’t the answer. Your analysts need better tools to speed up data preparation efforts that ultimately lead to faster, deeper insights that matter to the business.

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Building Highly Agile, Impactful, and Respected Analytics Centers of Excellence

To become a ‘data-driven’ organization, companies are rapidly setting up analytics centers of excellence. But they are doing so in a way that unwittingly prioritizes software training and procurement over tackling broader organizational challenges. Join Blue Hill Research’s Principal Analyst James Haight and Lavastorm CTO Mark Marinelli as they discuss research into the mindset, strategies, and techniques needed to build successful analytics Centers of Excellence.
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The Agile Solution for Successful Analytics Centers of Excellence

Most Analytics Centers of Excellence do not deliver results. To address these challenges, Blue Hill Research conducted deep primary research with leading consultancies, systems integrators, and multi-national companies to understand how to construct successful analytics CoEs.

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Lavastorm Overview Data Sheet

Lavastorm powers enterprise-grade business applications with self service data preparation and agile analytics to help businesses gain a competitive advantage by unlocking the potential of their data. Click here to for an overview of Lavastorm.

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Breaking Through your Data Bottleneck with Agile ETL

Listen to our webinar recording to learn where traditional ETL tools and waterfall projects are not a viable solution for modern analytics. Alternative technologies are now available which marry self-service data preparation with enterprise data management capabilities to accelerate value delivery, without reducing the scale, scope, and rigor of data analysis.

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Investing in Agile Analytics Expansion

To achieve data-driven differentiation, organizations must overcome complex data challenges, contending with social, mobile, and IoT-enabled data sources that drive new technology investments. Blue Hill’s James Haight and Hyoun Park investigate the decision-making and operational process of organizations that have succeeded in navigating such environments.

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Agile ETL for Visualization

The explosive growth and adoption of interactive visualization products, such as Tableau, QlikView, and Spotfire, has been driven by the need for business users to access data, perform analysis, and publish results with less dependence on scarce technical resources. Take your data visualization investment to a new level of productivity and impact through agile and transparent ETL and advanced analytic capabilities.

 

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Balancing the Demands for Business Agility with IT Governance and Control

Data discovery is upending the traditional BI approach by empowering users with the capability to combine and analyze data on their own, independently from the IT organization. The need for business agility and self-service analytics is changing the governance equation. Finding the right balance between business agility and IT control or governance is, therefore, essential to having an effective self-service analytic initiative.

 

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Drive Business Insight With Effective BI Strategy

How does BI differ from reporting and management information systems? This road map will give you an understanding of the four critical steps in strategizing around BI to achieve business goals: 1) establish the value of BI; 2) set the right strategy; 3) execute the strategy with precision; and 4) measure and optimize results.

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Build An Agile BI Organization

This report provides an organizational framework that describes how application development and delivery professionals working on BI initiatives can align their BI organization for agility; it’s a key part of Forrester’s Agile BI tetrad — Agile BI software development, organizations, processes, and technologies.

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Unleash the Power of Tableau

Tableau’s stunning success has empowered individuals across the enterprise to create powerful data visualization and analysis on-demand. However, the challenge lies in the time and effort it takes to prep data for visualization.

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Democratizing Data & Predictive Analytics Software

As organizations empower more users to fully leverage advanced and predictive analytics software to “democratize” their data and bring insights to the masses through interactive visual dashboards, they also need to provide enhanced data transparency, collaboration, and governance to gain broader acceptance and trust of the data.

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Citizen Data Scientists: How Self-service Tools Can Democratize Data

The tsunami of valuable data has hampered the ability of the few highly skilled technologists to take advantage of it. To bridge the gap, more and more companies are providing advanced analytics tools to its super users – a group Gartner calls “citizen data scientists”

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Linking together reactive and proactive data iteration

This firm sought an efficient and transparent visualization process to support their growing data needs and gain a competitive sales and market advantage using agile business analytics for big data.

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Optimizing Service Delivery

Read this case study to see how tw telecom uses Lavastorm to optimize their service delivery and eliminate customer billing issues.

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Building a Best-in-Class Finance Organization with Agile Analytics

Lavastorm provides Telia with agile data management, integration, and analytics capabilities. Faster Response Time, Higher Revenue from Partner Relationships, and Reduced Services Costs.

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Transforming the Audit Process

Read this case study to see how PwC uses Lavastorm to dig deeper, broader, and smarter.

 

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Overpowering Data Quality Issues and Massive Data Volume Increase

See how E.ON used Lavastorm to eliminate data gaps, clean up data quality issues, reduce management reports, get more value out of their BI investment, automate data quality improvement efforts, and improve management team understanding of data quality initiatives.

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Data Quality

See how a major Asia-Pacific telecommunications company uses Lavastorm to uncover data quality issues and continuously improve data quality and other business results.

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Data Migration

See how a major Asia-Pacific telecommunications company uses Lavastorm to migrate data faster than SQL methods, perform rapid root cause analysis to speed resolution, provide visual assurance of data and process integrity, and process accurate data transformation on a massive scale.

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Implementing Data-Driven Loss Prevention

See how Compass Group uncovers potential theft using data from 2,300+ locations, improves success rate of investigations, makes better use of its auditing resources, improves its ability to prove cases in court, quickly monitor and identify errors, and improves loss prevention company wide using Lavastorm.

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Mastering Data Quality Management

Read this case study to see how Allstream improved their data quality management and sales performance with the Lavastorm.

 

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Five Ways to Empower Business Analysts & Succeed in Your Self-Service BI Program

Many BI projects fail when not controlled by the business. Lack of proper requirements gathering and the inability to meet the needs of users creates a lack of adoption. Simple tools such as Excel and Access can no longer handle the complexities and increasing volumes inherent in big data or maintain the validity of analytic models. Read this new Lyndsay Wise paper for a look at five key enablers of self-service BI for business analysts.

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Optimizing Financial Processes: Consolidation and Reconciliation

Finance departments find they are struggling to be agile and quickly address changes in the business and data flows. Manual processes, and business inefficiencies are just some of the just some of the challenges that you face. Lavastorm was introduced and the finance employees were able to utilize it to connect to the disparate data sources, prepare and blend the data, and output consolidated data, while simultaneously improving monthly reporting process.

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Solving Data Integration Challenges with the Lavastorm

Accessing, preparing, and integrating data from different sources is usually the toughest part of any analytics project. Inconsistent formats, missing data, inaccurate data are just some of the problems that you face. Lavastorm wipes away those common data integration problems with a streamlined approach to acquiring and combining just about any type of data – 10x faster than other methods.

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Regulatory Reporting for Financial Services

Financial services firms face an increasing regulatory burden. Reports need to be more detailed, comprehensive, and accurate – and delivered more quickly. Compliance is a struggle using spreadsheets and inflexible legacy systems. A new solution is needed. Lavastorm Analytics software lets firms quickly create auditable regulatory reports. Business users can aggregate data, check data quality, analyse data, and generate reports – all without expensive and time consuming IT efforts. Plus, Lavastorm provides the flexibility to handle ad hoc requests and changing requirements while simultaneously strengthening IT governance efforts.

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Optimizing Trade Operations

When the global financial crisis occurred in 2008, a tidal wave of new regulation hit large financial institutions and weakened the traditional levers that were available to improve Return on Equity (RoE). As a result, a new imperative emerged: cost reduction through improved operational efficiency. In this environment, the demand for greater visibility into operations has never been greater and data and process analytics have become critical for identifying operational inefficiencies and eliminating the financial risks they create.

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Optimizing ROl using Agile Analytics

Retailers are facing the challenge of trying to increase profits in the face of fickle consumers and rising competition. To meet this challenge, you must know more than your competitors and understand customers better than you ever have before. This requires a fundamental advantage in how you acquire, manage and analyze data –and that requires Lavastorm.

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Enhance and Extend your Fraud Management System

Enhance your Telco’s Fraud Management System with Lavastorm. This Use Case shows how Lavastorm can augment your current FMS, giving you the ability to keep pace with the rapidly changing fraud environment, minimize your costs and deliver rapid ROI.

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Agile Revenue Assurance

Competitive and market pressures along with the need to prioritize the customer experience mean that Communication Service Providers (CSPs) must drive business performance optimization with more speed and agility than ever before. This Use Case shows how the Lavastorm can improve revenue assurance speed to resolution and accuracy of results, adapt quickly and gracefully to change, and benefit from significant ROI to increase business value.

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Agile Analytics For Smart Utilities

Lavastorm’s visual, discovery-based environment allows utility companies to reduce analytic development time by 90% or more and build iterative analytic models that help design and validate high performing business processes.

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Why Most Big Data Projects Fail

Organizations need to make big data analytics an integral part of their everyday workflows, which means continuously running analytics and automating processes. For this to work seamlessly, organizations need to tear down the walls between IT and business, remove hurdles, to strike a balance between demands for business speed and agility with IT governance and control. Tools such as Lavastorm help organizations capture big data-based insights while enabling a more agile and analytics-driven business culture.

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How Pharmaceutical Companies Can Automate & Improve Compliance Reporting

The Sunshine Act has added another layer of regulatory complexity for healthcare and pharmaceutical companies. Traditional tools cannot effectively manage this process, and require large investments of time and resources. Automating the data collection, analysis and reporting process with advanced end-user tools like self-service data preparation and advanced analytics is a better, faster, cheaper way to meet strict compliance requirements.

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Four Situations Where You Need Agile Data Management

Enterprises awash in data often struggle to answer basic business questions because they can’t supply data to the people who need it, when they need it. Situations where you’re dealing with, exploring external data, changing data sources, adjusting business logic and changing data fields are all desperate for agile data management. Organizing, prepping, transforming, and provisioning useful data shouldn’t be difficult. In fact, it isn’t: if you’re using the right tool. And that’s what agile data management is all about.

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Five Ways to Improve Data Prep for Tableau

The demand for Tableau and its ability to transform walls of spreadsheets into interactive and visual dashboards is not slowing down. However, the strength of Tableau relies on the quality and breadth of the data inputted. Helping users prepare, transform and deliver the most accurate and up-to-date information is critical to leveraging your dashboards and the data behind them. Learn 5 ways to improve the data quality you feed to Tableau.

 

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Breaking Through the Analytic Limitations of Access and SQL

Although they are often a cornerstone of a company’s analytic toolkit, traditional databases, such as Access, and query tools, such as SQL, are designed for storage and simple queries, not for creating the complex analytics that are required by today’s fast-moving businesses. New technologies can help organizations get over the analytic limitations of Access and SQL- especially when dealing with the demands to processing more data, changing analytics more frequently, and making analytics available to more decision makers.

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Breaking Through The Analytic Limitations of Access and Excel

Although they are often a cornerstone of a company’s analytic toolkit, tools like Access and Excel are designed for data storage and basic analytics, not for creating the complex analytics that are required by today’s fast-moving businesses. New technologies can help organizations move past the analytic limitations of Access and Excel, especially when dealing with the demands of processing more data, and making analytics available to more decision makers and stakeholders – all at greater speed than ever before.

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Empowering the Citizen Data Scientist with Self-Service Advanced Analytics

The growth of social media, the Internet of Things, and digital business is dramatically increasing the volume, velocity, and variety of data flowing into business organizations. Most businesses recognize the value of detailed information about customer and operational activities, but establishing and managing a process to convert the mass of data into actionable decision-making can be daunting.

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Powering The Energy Industry With Advanced Analytics

In the traditional consumer billing model, customers pay a fixed monthly fee for their connection and a transport fee per/kWh of electricity regardless of when they use it. This creates peak loads on the grid at various times of the day and underutilization at others. This fluctuating demand forces the need for capital investments to handle peak load activity.

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Agile Salesforce.com Analytics

Integrate cloud-based data sources, such as Salesforce, with your enterprise data sources for improved decision making and visibility. This solution brief discusses the “data gap” that cloud-based data sources can cause and how Lavastorm Analytics can bridge that gap.

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How to Find Happiness in your Data Warehouse Architecture

When organizations want to improve data quality, organize data for analytics, or develop a “single version of the truth”, they immediately think they need to start with a data warehouse architecture. But when is using a data warehouse architecture the wrong move? When FairPoint Communications wanted to organize data from far-flung parts of the company, they turned off their data warehouse architecture in favor of an agile data management and analytics solution that acts as a virtual data. The alternative approach brought agility to their organization and transparency that benefited decision makers in all departments.