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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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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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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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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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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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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.