What We Do
Our experienced big data experts can help you manage your structured and unstructured data, and improve processes and reporting capabilities. Our dedicated big data staffing specialists can mobilize big data teams quickly to meet your mission-critical IT staffing needs.
Besides our focus on 3 Vs (Volume, Velocity and Variety), we also consider V “Veracity” and V “Value” of the data as well as additional best-practices from enterprise class information management strategies that will ensure Big Data success.
We use statistical sampling to clean, enrich and deduce unstructured data and revalidate the content structure upon every recipe periodically, manually or automatically.
Our big data experts can deliver the POC (Proof of concept) to include the details of Business use case, New technology understanding, Enterprise integration and operational implications. We also help with cross train the consultants to acquire the needed open source skills to handle the Big data projects.
Beyond estimating the basics, such as storage for staging, data movement, transformations, and analytics processing, we also help you how the new technologies can reduce latencies, such as parallel processing, machine learning, memory processing, columnar indexing, and specialized algorithms. In addition, we also help to distinguish which data could be captured and analyzed in a cloud service versus on premises.
Unique distributed (multi-node) parallel processing architectures have been created to parse the large data sets. There are differing technology strategies for real-time and batch processing storage requirements. For real-time, key-value data stores, such as NoSQL, allow for high performance, index-based retrieval. For batch processing, a technique known as “Map Reduce,” filters data according to a specific data discovery strategy. After the filtered data is discovered, it can be analyzed directly, loaded into other unstructured or semi-structured databases or merged into traditional data warehousing environment and correlated to structured data.
We make sure to align the Big Data security strategy with the enterprise practices and policies already established, avoid duplicate implementations, and manage centrally across the environments.
The physical separation of data centers, distinct security policies, ownership of data, and data quality processes, in addition to the impact of each of the 5 Vs requires architecture decisions. So, this begs an important distributed processing architecture.
TekBusiness has taken an integrated approach across a few of these areas. We audit database traffic to detect and block threats, as well as improve compliance reporting by consolidating audit data from databases, operating systems, directories, file systems, and other sources into a secure centralized repository. From data access standpoint, Big Data SQL enables standard SQL access to Hadoop, Hive, and NoSQL with the associated SQL and RBAC security capabilities: querying encrypted data and rules enforced redaction using the virtual private database features. Our enterprise design goal is to secure all your data and be able to prove it.