Caci Data Tactics Corporation

Our Mission

Design, develop, deliver and manage First to Market, data-oriented capabilities for our clients' enterprises.
Execute first to government market academic and commercially sourced data solutions/trends while highlighting customer relevancy.
Execute and deliver superior services across the customer's enterprise lifecycle.

Our Vision

To establish an enduring relationship of trust with our client based solely on our performance.
To deliver a product or service that becomes second-nature to our client's personnel and a seamless part of our client's business operations.
To remain a creative, disruptive and leading research, development and rapid deployment institution where our shared intellect, hard work and vanguard for our client's trust make a positive difference in the lives of our employees, the success of our clients and the security of our country.

Big Analytics - Geospatial Intelligence Forum

Data analytics for geospatial intelligence have reached a crossroads at
the convergence of big data and cloud computing. The junction is filled
with diverse data sources and emerging technologies driving toward the
ultimate destination--a cloud-based, integrated analytic environment,
partly accessed in real time.

In the meantime, there are many steps along the way, starting with
the spreadsheet and shapefile data format still commonly used today,
and moving to GIS tools and relational or SQL databases housing
structured data, as well as statistical analysis software used
to perform increasingly complex queries of data. A crucial step is
the growing use of "not only SQL" (NoSQL) databases, providing
access to previously unreachable, unstructured data and expanded queries.

Data Tactics Analytics Practice

The precise nature of analytics is a common source of debate, if not confusion.
Data Tactics contributes to the analytical space as well as complimentary areas of data exploration and inquiry, qualitative analysis and information discovery and retrieval. The main source of confusion is these other modes of inquiry hold value, but cannot generate the same insights or solve the same problems as analytics.

A positive definition for analytics is one that clarifies the scope, role and
value of analytics especially vis-?-vis the data analysis frameworks mentioned above, with a focus on their difference and mutually reinforcing aspects.

Analytics is relational and probabilistic. Analytics is relational in that
it focuses on associations, rather than examining single variables or characteristics.
Rather than asking, "List all of the items in X with characteristic A," an analytical question would ask "What is the relationship between characteristics A and B within the group of Xs?" This focus on relationships makes analytics uniquely useful for identifying patterns within and between variables, as well as observations that do not fit these patterns (i.e. outliers). Identifying patterns which are pervasive and represent smooth qualities of data, as well as those that do not fit smooth patterns, analytics can serve as a data reduction tool, turning terabytes of data into short lists of important observations and/or attributes.

Analytics is probabilistic, in that the relationships it identifies between and among variables hold on average, but do not necessarily hold for every individual observation. This allows for predictions to be made for observations with missing data, as well as forecasts into the future. The probabilistic nature of analytics allows for the quantification of uncertainty. Beyond predicting, for instance, that a particular location serves as a base of operations for a rebel group, analytics provides a measure of the uncertainty in this estimate. For instance, maybe an analysis predicts that the village has a 64% chance of being the rebel base of operations, plus or minus 4%. This explicit quantification of uncertainty is important for decision makers using analytics to inform policy choices.

Analytics can be usefully contrasted to qualitative analysis and to information retrieval (i.e. deductive or query-based) analyses and the differences prove to be more than just a normative preference. Qualitative analyses usually focus on one or a small number of observations, whereas analytics is best suited for analyzing large sets of data. Qualitative analysis allows for a very deep understanding of a few observations, whereas analytics provides evidence of patterns among and between variables. When done correctly they both are independently powerful tools. Analytics
however, is preferable when data exists in quantity because of its ability to harness data, rather than being overwhelmed by it.

Database-driven analyses akin to information retrieval can provide deterministic analyses based on Boolean logic; for instance, "Show me all observations of group A with characteristics X and Y." This is useful for identifying observations with certain characteristics if the question
is known in advance. Analytics is most useful for evaluating the strength of relationships between characteristics. An analytics approach might be to describe the relationship, on average, between characteristics X and Y within the population of As.

Cloud Computing

Current global military operations require data systems to be agile and flexible. Complex data mining architectures have become a staple for both tactical elements and analysts. Data Tactics architects computing models that enable convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Clearing up the Cloud

Cloud: One small word that covers so many technologies--Public Clouds, Private Clouds, Virtual Private Clouds, Platform as a Service (PaaS), Software as a Service (SaaS), Software as a Service (SaaS), Infrastructure as a Service (IaaS),Data Center as a Service (DaaS) and Big Data. Data Tactics cuts through the fog to deliver more than just buzz words. We assist your organization in developing a solution that meets your operational needs.

Global Operations require Global Scalability

As the scope of the mission grows, the information infrastructure that supports that mission must grow as well. Today's global operations require technology capable of delivering services to a distributed, dynamic, and highly-mobile user community anywhere in the world.

Vendor Agnostic Approach

Which approach is best? How will you control your information after it enters the cloud? What can you do to prevent lock-in with a single vendor's cloud offering? Whether your organization is looking to become a cloud provider, move a legacy application into a service approach, or something in between, Data Tactics can ensure the approach you take will benefit your organization for years to come.

Securing Cyberspace

Data Tactics provides comprehensive Cyber Security services that assess and implement integrated physical, technical, operational, and communication security requirements and disaster recovery, including: Security Architecture, Design, and Configuration Certification and Accreditation
Compliance Audits and Inspections Operations and Life-Cycle Support
Penetration Testing and Intrusion Detection/Prevention Policy/Process Development and Validation Risk/Vulnerability/Consequence Assessments and Management

Proactive Cyber Security

Today's leaders face multiple challenges, including the need to be innovative in extremely competitive conditions, address dynamic regulatory and compliance challenges, speed returns on investments (ROI) to counter shrinking budgets, and secure the enterprise against a barrage of evolving sophisticated threats. Data Tactics' holistic approach to cyber security helps you address risk and reduce cost and complexity to meet business and regulatory requirements.

Intelligence Analysis

Data Tactics Intelligence Analysis capability successfully implements an Analytical Planning and Delivery Process (APDP) that converts acquired information and data into clear, comprehensible intelligence and delivers it to the decision makers and military commanders in a form they can utilize to make educated decisions and set clear courses of action. Generating reliable, accurate intelligence is a never-ending process commonly referred to as the intelligence cycle.