Data is the new oil, where companies and individuals are getting unrivaled benefits from the data science. If you are looking for a company to provide you top-notch services, have a look at our compilation of top 10 data science development companies in Seattle.
Zazz is a team of creative designers and developers building great digital products in Seattle and San Francisco. Our collective experience in the technology industry includes mobile app development, IOT application development, blockchain development with a design first approach to product development.
Appstudio is a full service Mobile App Design & Development Company offering services in Native iOS Development (Swift 3.0), Native Android Development (Java), React Native Development & Unity Game Development. They have collaborated with Fortune 500 companies, Startups and Mid Sized firms across a spectrum of industries, ranging from Health Care & Finance to On-Demand Services, to create Mobile apps that are actively being used by Millions of users across the globe.
Neudesic is the trusted technology partner in business innovation, delivering impactful business results to clients through leading-edge technologies, innovative solutions, and strategic alliances. Founded in 2002 and headquartered in Irvine, California, Neudesic is a privately held company, serving clients globally from offices across the United States and India.
Microsoft Dynamics AX CRM With over 100 years of cumulative ERP experience, we have Industry-Tailored Microsoft Dynamics AX Solutions to fit the specific needs of Consumer Packaged Goods, Manufacturing, Retail, Wholesale Trade: Durable Goods, Wholesale Trade non-durable goods and Distribution.
Inspirage is the integrated supply chain specialist firm solving business critical challenges from design to delivery. The company delivers end-to-end consulting and implementation solutions that link Product Lifecycle Management, Supply Chain Management and Logistics Management.
CloudMoyo is the partner of choice for solutions at the intersection of cloud and analytics. We help modern enterprises define their path to the Cloud and leverage the power of data driven insights.
47 Degrees is a global consulting and development firm specializing in helping clients take the next step in modernizing legacy applications to be real-time, secure, and responsive, by using battle-tested functional programming and cutting-edge technologies including Scala, Kotlin, Swift, Spark, Kafka, Akka, and Cassandra.
At Metia, we create amazing experiences, ignite conversation, activate communities, inform customers and influence decision makers.
Virtuozzo is a leading hyperconverged infrastructure software provider with integrated container, virtual machine and storage solutions. Virtuozzo developed the first commercially available container technology in 2001, and today has more than 5 million virtual environments in production.
Hello! We're analytiks, a Seattle-based data company. And we want you to know that even though it's extremely cloudy here in Seattle, your data doesn't have to be. From long-term, end-to-end big data management, to jumping in and driving quick wins for your business - we'll provide you with the data solutions you need to drive more revenue to your bottom line. No matter where in the US you're located.
New Generation Analysis: Data Science
While Big Data focuses on providing tools and techniques to manage and process large and diverse amounts of data, it is not so focused on interpreting the results of data processing to support decision making. This is where Data Science comes in, focusing on the use of advanced statistical techniques to analyze Big Data and interpret the results in a specific domain context. Therefore, Data Science involves an intersection of several areas that include:
- Data Engineering
- Advanced Computing
- Domain and others
Within this context, tools and frameworks are required to:
- Statistics Programming
- Import and clean data
- Exploratory data analysis
- Machine learning
- Deep learning
- Text Mining
- Natural Language Understanding
- Recommendation Systems, etc.
In general, Data Science focuses on providing a comprehensive solution to obtain valuable information to support decision-making in the fast and heterogeneous context of modern data management and analysis.
Current Panorama: Data Lakes
Thanks to social networks, personal mobile devices, sensors and other data intensive applications and devices, even small and medium-sized businesses had the opportunity to obtain large volumes of data about their businesses and customers. Here, Data Lake emerged as a typical solution to manage and analyze Big Data in that context.
When you have heterogeneous data sources that include unstructured (for example, social media) and / or semi-structured (for example, email), Data Lakes (usually an HDFS-based solution) It presents flexible data management where data can be ingested. Ideally, Data Lake can also include a metadata layer that describes data organization and semantics (for example, through the use of semantic technologies).
Once collected and stored, the data can optionally be prepared (for example, by creating tables and / or matrices) for data analysis (for example, visualization techniques or machine learning). Finally, the use of Data Lake supports batch data processing (following the complete arrows), that is, the data is stored and then processed for report support, and can also be coupled with the components for processing the data.
Benefits of Data Science
The generation, analysis and interpretation of data has a great potential for development in medicine, for example, since the use of Machine Learning algorithms for diagnosis and analysis allows to improve the prediction of conditions. From the hand of the digitalization of the available information and the crossing of data it is possible to learn about the diseases, to know in what conditions they can appear and even to detect their symptoms previously.
As in all cases, more information and data will result in better results and more knowledge in preventive health. In particular, interoperability between the different institutions would present great advantages and for that it would be necessary to generate common standards and a database with the information of all patients.
Education and Data Science
In education, the application of Data Science and Machine Learning allows students to explore their abilities and know their reactions to different stimuli to know which ones are more effective. The identification of learning needs from the analysis of performance and results also makes it possible to choose the optimal educational content and modalities to facilitate and promote the learning of each student.
Some companies are already making progress in this regard: Microsoft developed Azure Machine learning to help Indian educational authorities predict school dropout with information on student performance, school infrastructure and teacher skills.
Marketing, Advertising and Data Science
Another area in which tools for data analysis and machine learning are being successfully exploited is marketing and advertising. Big data allows you to customize the advertising that each user sees on social networks and makes streaming platforms suggest what content to keep watching according to the preferences of the person watching, but those are only the first steps.
Amazon uses Machine Learning technology to recommend new products to its users and its automatic systems have a high percentage of success in anticipating the purchases that their customers will make. Reading responses to an advertisement or a product, the prediction of the rotation of the clients and the selection of cases of better and worse results allows companies to know that are the most appropriate ways to achieve their objectives and improve the services. Having a better knowledge of the public and anticipating their needs also allows to personalize and improve the experience of each consumer in the exchange. Thus, data becomes an engine for marketing and advertising, but it also allows you to optimize the operation of each business by detecting what are the most and least used resources and what are the results obtained with each of them.
Retail and Data Science
There are several advantages of the use of Machine Learning and Data Science in retail, especially for those businesses that have a loyalty system that allows to have the data of what and how much each customer buys, know their tastes and preferences and improve and simplify your shopping experience.
Artificial intelligence has gone so far that it allowed Amazon to develop an automated store, Amazon Go, a path that was followed by Walmart: there customers take the products from the gondolas and withdraw without going through a box, since the process of Collection is made through the Amazon app with an incredibly accurate and reliable system. The generation and analysis of data also allows predicting the needs and behavior of customers,
Finance and Data Science
In the finance sector, data analytics and artificial intelligence are already used, which allows us to know the patterns of customer behavior, anticipate certain situations and improve responses to new conditions. In addition, data analysis is an opportunity to anticipate or reduce financial risks, not only for the company, but also as a service developed for customers. Having information about customer behaviors allows financial institutions to generate new business opportunities and anticipate the needs and demands.
On the other hand, working with other external databases may also allow them to increase the number of customers or discover opportunities for the development of new products. Further, Data Science techniques can be used to know, for example, where to locate branches or ATMs, how much money to enter in each of them or to know what areas of attention should be strengthened in each area. The development of new forms of communication with users is also an opportunity to use these tools to improve and expand their potential.