Atom Data Services™ implements Big Data analytics and Machine Learning solutions through the process that provides past, current and future statistics and deep insights that lead to informed business decisions and timely actions.
In the age of big data, finding an effective way to process rich data and enable analysis which will eventually provide insights that lead to best business decisions and actions, becomes a major challenge for many organizations. Atom Data Services use proven technologies to provide solutions and services that empower companies and organizations to gain from deep insight into their data and utilize them for timely actions. Services provided by Atom Data Services solve problems with data volume, which could be measured in terabytes or even petabytes. At the same time, those services and solutions deal with data velocity where data is rapidly changed, and variety where data is unstructured or semi-structured.
Our solutions are hosted online, typically using Amazon Web Services (AWS) or Microsoft Azure cloud tenants. Atom Data Services solutions use both cloud platforms equally well, and we leave that choice to our customers, based on their IT strategy and preference. In some instances, when confidentiality and privacy require data not to leave the realm of an organization, we also provide on-premises solutions, utilizing client’s own infrastructure.
Some of the most successful implementations under Atom Data Services belt used Spark for processing of big data. Spark offers cost-effective data processing at scale using affordable hardware or low cost virtual machines. It is an in-memory cluster computing framework and it provides a simple programming interface which our developers extensively utilize to make use of the CPU, memory, and storage resources across a cluster of servers.
Atom Data Services recognize some key benefits of Spark...see more
Some of the most successful implementations under Atom Data Services belt used Spark for processing of big data. Spark offers cost-effective data processing at scale using affordable hardware or low cost virtual machines. It is an in-memory cluster computing framework and it provides a simple programming interface which our developers extensively utilize to make use of the CPU, memory, and storage resources across a cluster of servers.
Atom Data Services recognize some key benefits of Spark:
ADS is a predictive analytics company helping leaders to effectively manage their business by providing actionable insights from internal and external sources of data.
Our expertise in applied data science along with extensive proficiency in collecting, storing and managing data, has been built-in into our agile and scalable platform, ready to answer your needs at unrivaled speed and accuracy.
We are solving the problems caused by lack of adequate and timely insights.
Atom Data Services team is led by experienced Data Scientists and Data Analysts combined with a strong group of Java and Web developers that are delivering a variety of solutions for government related services, public sector, telecommunications, and utility companies for the last two decades.
Atom Data Services has a long tradition in building tailored data solutions ..in addition
Strong demand for reliable and easy to use data solutions for various utility ..in addition
Driving factors for Atom Data Services platform selection are high availability, scalability, and fault tolerance at a lower cost.
One of the platforms that was early embraced as a popular big data technology is Hadoop. As a scalable fault-tolerant system for processing large datasets across a cluster of affordable, commodity servers, it was a good fit for Atom Data Services approach. The fact that Hadoop uses scale-out architecture, where a cluster of commodity servers is used for storing and processing large amounts, provides much lower cost that the scale-up architecture. Another contributing factor is that implementation of software fault-tolerance is far less expensive than implementing it in hardware fault-tolerance servers.
Atom Data Services software developers take advantage of Hadoop framework to produce distributed applications in a much simpler and faster way than standard development approach. Hadoop Distributed File System (HDFS), MapReduce, and YARN provide all necessary building blocks for successful big data solutions. The MapReduce framework automatically schedules an application’s execution across a set of machines in a cluster. It handles load balancing, node failures, and complex internode communication. It takes care of the messy details of distributed computing and allows a programmer to focus on data processing logic.
Another software in our toolset is Hive. It provides our software developers with Hive Query Language (HiveQL) which is a powerful language for processing and analyzing data stored in Hadoop or compatible systems like Cassandra or Elastic. This is yet another way of using MapReduce in a simple manner.
Our data solution development approach always considers the best technology for a client or project. For that reason, we carefully choose technology so that it matches needs and goals of the project. In a wide range of NoSQL platforms, we use Cassandra as a distributed, scalable, and fault-tolerant database designed to for storing large datasets. It is particularly useful when ever we expect large volumes of data inserts, because that’s what Cassandra is optimized for.
Some of the most successful implementations under Atom Data Services belt used Spark for processing of big data. Spark offers cost-effective data processing at scale using affordable hardware or low cost virtual machines. It is an in-memory cluster computing framework and it provides a simple programming interface which our developers extensively utilize to make use of the CPU, memory, and storage resources across a cluster of servers.
Atom Data Services recognize some key benefits of Spark:
Spark’s ease of use comes from a rich application programming interface (API). It provides more than 80 data processing operators, which makes it more expressive than other similar platforms. Spark makes its cluster computing capabilities available to an application in the form of a library. Libraries can be written in all Spark API available languages, such as Scala, Java, Python, and R.
Another feature that makes Spark attractive to our development practice is its immense speed. It is orders of magnitude faster than Hadoop MapReduce, which measures in hundreds of times in some cases.
We appreciate Spark’s scalability, because processing capacity of a cluster can be increased by simply adding more nodes to a cluster. That enables us to begin with a small cluster, and as dataset grows over the time, we can add more computing capacity. Scaling that way is not only smart, but also economical.
Our solutions utilize Spark not only for batch processing, but also for machine learning, graph computing, stream processing, and interactive analysis. That’s how we can use one framework for a variety of purposes, thus avoiding multi-platform challenges and increasing efficiency of our team.
In a cluster of a few hundred nodes, the probability of a node failing on any given day is high. Spark is fault tolerant, and automatically handles the failure of a node in a cluster.
Atom Data Services implements Big Data analytics and Machine Learning solutions through the process that provides past, current and future statistics and deep insights that lead to informed business decisions and timely actions.
Our stellar reputation of a reliable partner who always delivers high quality Big Data Analytics and Machine Learning solutions and services, made Atom Data Services to be the first outsourcing choice for our numerous partners. For that reason, majority of our projects is implement in partnership with other companies who seek to utilize Atom Data Services expertise for the benefit of their clients.
We are also proud to serve our government customers and deliver solutions involving terabytes or petabytes of data and high complexity algorithms. Information insights generated by Atom Data Services solution enable various government agencies to be very effective and execute target actions with high precision and efficiency.
Our team of experienced Data Scientists and Data Analysts combined with a strong group of Java and Web developers is delivering a variety of solutions for government related services, pubic sector, telecommunications, and utility companies for the last two decades.
Atom Data Services Big Data analytics and Machine Learning solutions are usually based on Apache Hadoop and Apache Spark frameworks. However, our team works with versatile platforms, such as Cassandra or Elastic, utilizing Hive for processing and analyzing data. We also take advantage of the latest Microsoft Azure cloud breakthrough and utilize Big Data Analytics hosted in Azure. High quality algorithms enable our customers to run fast processing and achieve 100x performance of regular MapReduce function.
Atom Data Services has a long tradition in building tailored data solutions for government agencies and other related entities. In more than two decades of experience in working with government, Atom Data Services team has designed and built systems that currently operate on petabytes of structured and unstructured data from heterogeneous data sources. Our team is trained and used to work with huge amounts of highly sensitive data sources and have vast experience in data de-personalization to address privacy and security concerns. We take huge pride in contributing government’s efforts to keep all citizens safe, consistently provide better service, and work transparently with optimal resource utilization.
Government effectiveness through informed, data based planning and targeted action with high precision and efficiency.
Enabling government to find a needle in the haystack with specific customize process, with intuitive visual experience.
Ingest raw data from various sources, process, persist and transform for exploratory and analytical delivery. Atom Data Services handle both structured and unstructured raw data and internally while processing received data through different stages convert them to useful information. Raw data enrichment with meta data connected information available for various target or key word searches or analytical drill down with custom defined process.
Raw data are converted to business useful information. This information is available on fast dashboards with high level analytics aggregations for the This process is done automatically in Atom Analytical Engine and is fully customizable: from raw data processing, creation of information, analytical aggregation on information and end user chart resulting in fast delivery of right information at the right time from Pb of row data.
Strong demand for reliable and easy to use data solutions for various utility companies drove Atom Data Services to design and develop proprietary AI prediction engines for power utility and water supply companies. The prediction engines are built on machine learning platforms and our algorithms achieve a high level of accuracy, based on actual trends and all utilization history. Artificial Intelligence solutions provided by Atom Data Services can reliably predict demand, price trends and incidents over a certain period, which in turn empowers utilities to gain a significant insight into market price oscillations or enables them to plan for maintenance activities and avoid emergencies.
By matching trends of production, available capacity, meteoritical and hydrological data, our models are empowering professionals to take more accurate and timely decisions.
By bringing siloes of data available in disparate systems, across different historical periods, professionals get better insight into equipment state, potential incidents and optimal maintenance windows.
Many factors are shaping utilities business, therefore data sources used for understanding environment are inherently complex, heterogeneous, multiple, and big. Atom Data Service have extensive expertise in collection of utilities data, and with our propriety solutions components we are capable to perform near real time consolidation, validation and unification of data into data storage as baseline for meaningful application of predictive models for optimization of business operations
All results as outcome of predictive models execution, are meaningful only if they are connected and used for a running business. Our components for standard reporting, KPIs and dashboards are first layer for delivering insights. On top, built-in module for statistical analysis and trends insights provides additional level of details, especially when combined with self-service analytics module. As final stage of integration ADS provides notification services and APIs for establishing interoperability with other solutions and people.
The needs and expectations of modern shoppers have dramatically changed over last decade. Necessity for personalized approach evolved in digital shopping are spreading across brick and mortar shops as well, and personalization is not possible without proper understanding of data customer is leaving behind with every interaction across all channels. Atom Data Services is helping retailers to retrieve and consolidate data, to create insights and manage front and back operations more effectively. Atom Data Services tools and solutions enable businesses to take on a journey of prototyping and scaling up most successful initiatives based on measured customer feedback and sales results.
By combing demographic data with history of customer purchases, our solution is recommending most appropriate products for a particular shopper.
Historical evidence and daily trends when properly matched, are optimizing inventory levels and procurement process, at the same time minimizing out of stock situations.
Historical data from shopping is used to segment customers based on their frequency of visit, monetary spending and regency, and based on that understanding to recognize particular offers which could in turn result in increased sales revenue. At the same time prediction of Customer Lifetime Vale helps retailers to identify customer profile and to adjust approach for the desired outcome. All of the calculations are fully dynamic, and all transitions among segments are additionally analyzed.
Based on customer segmentation and current situation (time, space, activity in place) our solution is able to initiate communication via specific component with customer through appropriate out of the list of available channels like – on-line web, chatbot, mobile app, SMS, e-mail, screens in shop or to provide sales staff with actionable insights. All of the campaign results are fully monitored and used as learning driver in continuous loop.
ADS collect information on various sources in telecom environment: CDR/IPDR, Raw Signaling information and generate business information about network congestion, subscriber anomaly detection, marketing package optimization, targeting subscribers for marketing offers across any channel. By processing such a large amount of data ADS helps telecommunication companies to better understand their end user experience and behavior patterns. ADS system is capable of monitoring both real time and post processing (offline) subscriber actions/faults. For example, drop call events in real time and reacting on it via available channels (inform network operations) or in offline processing raw data and generate data analytic reports about subscribers’ behavior or predefine marketing package offers, like subscribers that exceed their current package and are potential candidates for package upgrade offering.
Using different sources for gathering data, Atom Data Services solution generate network/subscribers information on current status, load, and congestions.
ADS analyze subscribers and generate reports for billing anomaly detection, next package offering when threshold is reach, subscribers that are loyal/sleepy/churners.
ADS solution analyze subscriber's patterns, experience, define clusters of subscribers with similar pattern in an offline process. It correlates that information with available marketing package offers and detects subscribers that are transiting from one segment to another, making them targets for marketing offerings.
Subscriber's network data monitoring, experience issues detection, alarm define channel for communication. Detail network data are available per incident: call record, signaling information.
