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10 Fastest Growing Data Analytics Companies 2017

Business Intelligence Engine for Big Data: Jethro

thesiliconreview-eli-singer-ceo-jethro-17Delivering Interactive Business Intelligence (BI) over Big Data is our passion and is our forte. Customers rely on Jethro to serve thousands of concurrent users analyzing tens of billions rows of data to support their business decisions. Actionable Business Intelligence mandates response time measured in seconds, up to date data measured in minutes, and data sets that span over 3 or more years of business.

Jethro Engine

Jethro’s BI acceleration engine offers Seamless integration; there are no changes to BI application or to underlying Hadoop Data Lake. Furthermore there is no need of manual data engineering, because Jethro automatically handles all of the costly, ineffective and endless data engineering. It offers Enterprise interactive Business Intelligence at Hadoop costs and BI dashboards respond in seconds on Big Data queries.

Jethro can support 1000s of concurrent users dicing and slicing 10s of billions of up-to-the-minute business data. It delivers such high level of service by computing user queries in real time from Indexes, cubes, and query caches that are automatically maintained and kept current by background services. Its Cost- Based Optimizer combines three different strategies to deliver interactive performance across all types of queries:

Full Indexing: every column is automatically indexed

Auto Cubes:  every aggregation is automatically turned into a small cube

Result Cache: every query result is automatically cached

Jethro System Architecture: BI tools send live queries to Jethro via ODBC / JDBC connection. Jethro servers can dynamically scale out to support any level of concurrency. All data—columns, indexes, cubes, cache—is centrally stored in Hadoop, cloud, or NFS, and shared by all Jethro servers.

The clients can focus on Interactive BI and save on costly busywork:

  • No table replication, no table partitioning
  • No wasteful hard to maintain flat (denormalized) tables
  • No manually built summary tables
  • No complex and tedious cube semantics
  • No change to 100s of existing applications
  • No manual work on incremental loads

With amazing performance, concurrency and ease Jethro Engine provides Seamless Compatibility with these BI, Hadoop, and Cloud platforms:

BI: Tableau, Qlik, MicroStrategy, and almost any other BI tool
Hadoop: Any Hadoop distribution including CDH, HDP, EMR, MapR
Cloud: AWS, Azure

Case study: Tata Communications

In 2006, Tata Communications, Ltd. launched the world’s first Content Delivery Network (CDN) for on-demand video and HD (High Definition) live video streaming. Today, Tata Communications’ CDN supports the whole spectrum of CDN (Content Distribution Network) services - including event live streaming, 24/7 online broadcasting, website acceleration, and large scale software downloads.

The Tata Communications Business Operational Intelligence Application

Tata Communication’s customers use the Business Operational Intelligence (BOI) dashboard to track their content distribution performance Key Performance Indicators (KPIs) across the entire CDN. The BOI dashboard tracks KPIs like traffic volume, response time, and browser type distributions - all measured across time-of-day and geography. Tata Communications clients rely on BOI when making business critical pricing, cost, and service level decisions. The Tata Communications CDN Data Lake is constantly loaded at 30 minutes intervals. The CDN lake grows every day by the volume of nearly two billion service requests captured daily.

After considering several BI products, Tata’s CDN team chose JethroData as their BI engine, naming the following reasons:

  • All queries results are swiftly computed from Jethro Indexes and cubes saving costly full scans of underlying data
  • Indexes and cubes are in fact a logical rather than physical repartitioning of data and therefore can deliver high query performance with no impact on co tenant applications
  • Most of the heavy lifting computing is done on data ingestions when building Indexes an Cubes, an investment that benefits all future queries that will use them
  • Indexes and cubes are updated on incremental loads, thus performance benefits are extended immediately to fresh data
  • Indexes and Cubes are created and maintained automatically, they do not impose any undue burden on administration
  • No data reengineering required thus no disruption to co-tenant applications and less risk to future releases of BOI
  • After a short POC (Proof of Concept) Tata’s CDN team adopted JethroData as their BI engine for their BOI application. The number of BOI users keeps growing and so does the daily data volume of captured CDN requests – BOI holds to its Service Level, responsiveness, and reliability.

Founders’ Desk

Eli Singer, Co-Founder and CEO: Eli is a serial entrepreneur with over 20 years experience leading private and public high tech companies. Eli was a founder of Memco Software (NASDAQ:MEMCF) and led it to a successful IPO and later an acquisition by CA. Eli co-founded and led WebCollage, the cloud e-commerce service of hundreds of the world’s leading retailers (acquired by answers.com). Eli is a business intelligence zealot and believes that interactive BI should be available to all business decision makers.

Ronen Ovadya Co-Founder and COO: Ronen has over 15 years rich experience running large customer projects for Amdocs a global provider of Telco Services. Ronen always was a hands-on user of Business Analytics making critical profit and loss decisions in a competitive market. Ronen believes that the BI that matters is the BI you have. He is passionate about automating the BI delivery processes and eliminating the costly busywork associated with them. Practical and cost effective BI is good BI.

Boaz Raufman, Co-Founder and CTO: Boaz is an expert in business analytics—he is specifically passionate about Big Data analytics performance. Boaz is leading the design and development of Jethro’s cost-based optimizer, Indexing and Cube management. He is the brain behind the machine. Before founding Jethro, Boaz led Big Data projects at Amdocs and the IDF Intelligence.

“Jethro Data customers enjoy actionable, business critical BI at the scale, scope, and speed of their business.”