The new federal law, Every Student Succeeds Act (ESSA), creates new opportunities to secure funding for language programming. Funding is available, but the strategies to secure the money must be carefully measured. Taking a strategic approach to this opportunity is critical.
Download the whitepaper to read more about the funding sources that should play into your strategies.
English Language Learners do not succeed at the same rate as their English-speaking peers. The impact is felt throughout the country: not only does it affect students, their families and their schools, it affects our communities. As the number of ELLs grows rapidly, the challenges increase. Today, a full 9 percent of this country’s population is not English proficient, and 11 percent of our K–12 students are considered English Language Learners.
Learn what districts can do to close this achievement gap in this infographic that paints the big picture.
Bernadette Musetti, Associate Professor of Liberal Studies at Loyola Marymount University has devoted most of her career to learning about and creating more equity and access in education for students whose primary language is other than English. In this white paper, she discusses how we can leverage technology to support ELL students and families for success.
Artificial intelligence (AI) seems to be on everyone’s mind. It powers natural language recognition within voice-powered assistants like Siri and Alexa, beats world-class Go players, and enables hyper-targeted e-commerce and content recommendations across the web, as we see with Amazon and Netflix. But recently, AI has begun actively expanding its footprint within the enterprise. Executives are trying to more fully comprehend what AI is and how they can use its insights into their data to better capitalize on business opportunities. This additional information can enable engaging with customers more productively and efficiently, forming an edge against the competition. Read more in our AI survey summary.
There is a lot of excitement in the market about artificial intelligence (AI), machine learning
(ML), and natural language processing (NLP). Although many of these technologies have been
available for decades, new advancements in compute power along with new algorithmic
developments are making these technologies more attractive to early adopter companies. These
organizations are embracing advanced analytics technologies for a number of reasons including
improving operational efficiencies, better understanding behaviors, and gaining competitive
Explaining what your company does can be a challenge. When your product is natural language processing, it can be outright difficult. Learn how the explainer video we produced for Inbenta helped to communicate their value to both customers and investors, but also increased online conversion rates by 20%.
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior-and profitable-interactions with customers. You'll learn: What it takes to uncover hidden trends and explore relationships across disparate data sources using natural language queries Ways to use in-depth insight to create highly relevant campaigns and content that's aligned with individual customer behaviors and preferences How to take product recommendations to new levels of accuracy with pinpoint prediction and targeting
Join IBM and partner Zementis in this webcast to hear how Predictive Model Markup Language (PMML), an industry standard, is helping solve business obstacles and enabling users to:
- Drive timely and relevant insights via in-line predictive analytics
- Score thousands of data records per second, scaling with business needs to enable instantaneous decisions
- Improve performance and cost efficiency by reducing or eliminating movement data off-platform to conduct analysis
ODM is the evolution of business rules management. It provides a complete, easy-to-use system for automating day-today operational decisions and allows businesspeople and IT to collaborate on business rules by using an interface and a language that are comfortable and intuitive for both.
ODM not only allows you to automate your business rules, but also it enables you to apply insights and analytics to operational decisions by bringing together data from different sources and looking at historical trends and patterns to determine the next best action. It ensures that you’re making the right decisions at the right time, when it can make a difference.
What can this mean for your business? Adopting operational decision management can:
• Improve customer centricity (acquisition and retention) by engaging individuals at the right time with the right offers
There are many types of databases and data analysis tools to choose from when building your application. Should you
use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right ft?
What about polyglot persistence and the need for advanced analytics?
If you feel a bit overwhelmed, don’t worry. This guide lays out the various database options and analytic solutions
available to meet your app’s unique needs.
You’ll see how data can move across databases and development languages, so you can work in your favorite
environment without the friction and productivity loss of the past.
Moving to C++ presents opportunities for higher programmer productivity. The requirements of embedded systems, however, demand that the adoption of C++ be carefully measured for the performance impact of run-time costs present in C++, but not in C. This talk suggests strategies for developers who are starting their acquaintance with C++.
No question the UI in electronic devices today is playing a larger role in the success of a device. Get the UI wrong and your product will have little chance of surviving. And it isn’t enough to deliver a UI that is merely functional: it has to look good too. Studies have shown that a good cosmetic design can encourage users to explore the full range of features and often, can engender the perception that a product is easier to use, which can make consumers more tolerant of product deficiencies. Learn more today!
"As the number of enhancements to various Hardware Description Languages (HDLs) has increased over the past year, so too has the complexity of determining which language is best for a particular design. Many designers and organizations are contemplating whether they should switch from one HDL to another.
This paper compares the technical characteristics of three, general-purpose HDLs.
How can you open your analytics program to all
types of programming languages and all levels of
users? And how can you ensure consistency across
your models and your resulting actions no matter
where they initiate in the company?
With today’s analytics technologies, the conversation
about open analytics and commerical analytics is no
longer an either/or discussion. You can now combine
the benefits of SAS and open source analytics
technology systems within your organization.
As we think about the entire analytics life cycle, it’s
important to consider data preparation, deployment,
performance, scalability and governance, in addition
to algorithms. Within that cycle, there’s a role for
open source and commercial analytics.
For example, machine learning algorithms can
be developed in SAS or Python, then deployed in
real-time data streams within SAS Event Stream
Processing, while also integrating with open systems
through Java and C APIs, RESTful web services,
Apache Kafka, HDFS and more.
Being responsible for one-third of a business’ success already puts HR in a critical role. But it’s not just about finding the best people—it’s about finding the best people, at the lowest cost, with the lowest possible attrition and the best possible performance. And it’s about guiding your executive team to the right decisions using the language they understand best: numbers. Talent management—covering everything from recruiting and compensation to ongoing education and retention—has traditionally been managed in silos, with a series of disparate systems and disconnected processes and reports. In today’s data-driven world, CEOs demand more. This new study conducted by HR.com explores what’s working for organizations today and the biggest gaps to fill.
If you specialize in relational database management technology, you’ve probably heard a lot about “big data” and the open source Apache Hadoop project. Perhaps you’ve also heard about IBM’s new Big SQL technology, which enables IBM® InfoSphere® BigInsights™ users to query Hadoop data using industry-standard SQL. Curious? This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.