The report is translated and reposted with the permission of Rusbase
Who to go to for the hardware, algorithms, consulting or ready-made solutions
In 2015, the global market of big data products and services reached $33.3 billion. American agency Wikibon provides this estimate in their March report. According to their forecast, by 2020 the big data market will top $61 billion, in 2026 - $85 billion. This market grows by approximately 17% a year.
Globally, Russian big data services and technologies market is embryonic. In 2014, American company IDC estimated it at $ 340 million. On the other hand, it is growing much faster than the global one - at a pace of at least 40% per year. According to some reports, in 2015 it will increase up to $ 500 million (this figure may be adjusted due to the devaluation of ruble).
It is known that big data existed long before the term even emerged. Search engines and social networks originally built their services on big data processing technologies. Today traditional business turned to big data as well. The utmost interest in data-mining is shown by the representatives of mature and highly competitive markets. They really need new tools to improve their efficiency. 40 out of 108 companies surveyed in February by CNews Analytics already started working with big data. The main buyers of such solutions are banks (24 out of 43 respondents) and telecom operators (8 of 12 surveyed). Big data technologies are also actively used in online advertising and retail.
According to the open sources, Sberbank, Gazprombank, VTB 24, Alfa-Bank, Otkrytie Financial Corporation, Raiffeisenbank, Citibank, Nordea Bank, Uralsib bank, OTP bank, Troika Dialog company, Russian Regional Development bank and Ural Bank for Reconstruction and Development, as well as major Russian telecom operators have all implemented big data technologies in their work practices. Large retailers such as X5 Retail Group, Gloria Jeans, Ulmart, hypermarket chain “Lenta”, M.Video, Wikimart, Ozon, Azbuka Vkusa along with such oil companies as Transneft, Rosneft and Surgutneftegaz use big data analysis tools to solve complex problems .
As for the public sector, where big data can give a real boost in efficiency, this set of technologies is hardly ever used. According to the experts, such government agencies as the Federal Tax Service, the analytical center of the Russian government, the Pension Fund, the Government of Moscow, Mandatory Health Insurance Fund, the Federal Security Service, the Investigative Committee and the Foreign Intelligence Service were the pioneers who integrated the technology. As for the big data revolution in the healthcare segment it’s still under way – the industry is lagging behind the other sectors in the data sphere, despite the paramount potential and accelerating value of the new tools.
Ahead of the conference on big data ICBDA 2015 we will tell you about the way the big data segment is formed in Russia. Our report is intended to give a general overview of the market, rather than compile an exhaustive list of players.
For the reader's convenience, we have divided big data market players into several categories (in fact, the boundaries between them are not so clear):
● Infrastructure providers that solve the problem of storage and data pre-processing (Sap, Oracle, IBM, EMC, Microsoft and others.);
● Dataminers - developers of the algorithms that help customers extract value from big data (Yandex Data Factory, Algomost, Glowbyte Consulting, CleverData et al.);
● System integrators who implement big data analysis systems on the client side (“Fors”, “Croc” and others.);
● Consumers who buy hardware and software systems and order algorithms from the consultants (telecom, banks, retail and others.);
● Developers of ready services based on big data (mainly digital marketing), which open big data capabilities for a wide range of users, including small and medium-sized businesses.
As for the data market in Russia, it is still in its formative stages, with development hampered by the overall economic downturn. Inside the RTB ecosystem the data suppliers are the owners of programmatic-platforms for data management (DMP) and data exchanges. Telecom operators share customer information about potential borrowers with the banks in the pilot mode.
Usually, big data comes from three sources:
- Internet (social networks, forums, blogs, media, and other sites);
- Corporate archives of documents;
- Readings of indicators, sensors and other devices
Naturally, the expert classification of the big data market players is much more complicated and looks somewhat like this:
They sell specialized database management systems, hardware and software systems and the associated analytical software - directly or through authorized distributors. The companies with their own expertise in the analysis of big data should be familiar with these products. Therefore, many prefer to rely on the system integrators and IT-consultants who select the hardware and software for the client’s needs.
German SAP entered the business analytics market in 2007, after it acquired Business Objects. Today its portfolio of big data solutions includes analytical database management system SAP Hana data and SAP IQ, SAP Hana in-memory database, SAP Event Stream Processing based on Hadoop, Lumira visualization tools and software for predictive analytics by KXEN (SAP acquired the company in 2013). The vendor is working with hardware manufacturers such as Dell, Cisco, Fujitsu, Hitachi, HP and IBM.
In Russia, the Federal Tax Service, the Pension Fund, the banking group “Otkrytie” and energy holding “Siberian Generating Company” use the SAP products. In October 2014, SAP launched a 9-month accelerator for the big data start-ups, four of the ideas were prototyped.
American Corporation sells a wide range of technologies for big data - specialized devices, database management systems, a variety of analytical applications. In 2014, Oracle acquired BlueKai, the cloud platform to manage big data, and received its arrays of unstructured information (the largest in the US market).
The vendor’s product lineup consists of analytical in-memory Oracle Database, Oracle MySQL and Oracle Essbase, Oracle TimesTen database in memory, Oracle Event Processing based on Hadoop, hardware and software solutions Oracle Big Data Appliance, Exadata and Exalytics. In Russia, the Oracle products are used, for example, by the Federal Tax Service and “Alfa-Bank”.
Last year IBM ranked first in Wikibon’s Big Data Vendor Revenue And Market Forecast ($ 1,4 billion). IBM sells the equipment to work with IBM PureData and Watson, DB2 database management system, a system for Hadoop BigInsights, InfoSphere data integration system, Cognos business analytics tools, SPSS and other products. The largest consumers of IBM big data solutions in Russia are the Pension Fund and VimpelCom Ltd.
The company offers a big data technology for business of any scale. Power BI tool is addressed for the small companies; it is included in Office 365 and built into Excel. The service includes public and corporate data catalogs, new tools for information retrieval, interactive visualization and wide range of opportunities for the collaborative work.
A number of big data solutions are available to users of cloud-based Microsoft Azure platform. For example, Azure Stream Analytics helps to process the information in the real-time mode, Azure Data Factory allows to retrieve information from various sources and to manage the data flow, machine learning tool Azure Machine Learning helps to make business programs.
Another Microsoft platform SQL Server allows you to manage any amounts of data in the cloud, or in their own infrastructure. The in-memory OLTP technology is implemented in SQL Server 2014, it increases transaction processing performance on average 100 times by selective migration of high load tables to RAM.
The US company specializes in software and hardware for data processing and analysis. The line of big data products include Teradata Data Warehouse Appliance, Teradata Aster Discovery platform and analytics software. The company also provides services for big data analysis. In Russia, Teradata solutions are used by the Federal Tax Service, VTB 24 bank, Sberbank and Citibank.
In 2013, EMC opened a division - Pivotal. It is engaged in processing big data and offers such solutions PaaS (platform-as-a-service) and ITaaS (IT as a service). For collecting big data Pivotal offers Greenplum database, query mechanism HAWQ for SQL on Hadoop (as the company claims, it’s the most functionally rich, mature and robust SQL offering available) and in-memory GemFire DBMS. In March, the company launched Federation Business Data Lake. In Russia, EMC solutions are used by Tin’koff Bank and the Troika Dialog company (now Sberbank CIB).
SAS is one of the pioneers of business intelligence. The company sells solutions for business analytics, data management and analysis. SAS offers customers consulting, implementation, training and technical support. Sberbank, Tin’koff Bank, UniCredit Bank, VTB 24, RZD and Tele2 use the company’s products.
SAS big data products solve different types of tasks. The product lineup includes distributed computing management technology - SAS Grid Computing, products based on in-database computing and products based on in-memory technology. The latter group includes the platform for interactive exploration and visualization of data - SAS Visual Analytics, interactive environment for data analyzing - SAS Data In-Memory Statistics, tool for creating the analytical models – SAS Visual Statistics, software for accelerated analytical modeling - SAS Factory Miner, SAS Event Stream Processing Engine for event flow analysis in real-time, text analysis engine SAS High-Performance Text Mining and other tools.
The company offers HP Haven cloud platform for big data, HP Vertica Community Edition database for creation of budgret-oriented products based on the processing of big data, HP Vertica Enterprise Edition - for larger projects, the HP Autonomy software - for the analysis of multiformat media (video, audio, social networks).
HP big data technologies are used for the analysis of Avito ad texts, ad targeting in online-cinema Ivi.ru, the analysis of customer behavior and transactions in real time by Otkrytie bank, the report automation by Gloria Jeans, the acceleration of product testing by Svyaz-bank. The first Russian buyer of HP Vertica analytic system became Yota Networks. By the way, HP Vertica solutions for the storage and analysis of big data are used by Facebook.
The California-based company sells the most popular open-source distribution kit of Hadoop framework. The full version of Cloudera Distribution Hadoop product includes software tools: Cloudera Impala, Cloudera Search, Apache HBase, Accumulo, Spark and Kafka. The company doesn’t have any hardware solutions. Last year, Intel invested $ 740 million in Cloudera. In Russia, Cloudera solutions are used by Sberbank and Tin’koff bank.
The corporation entered the business analytics market in 2012, by launching the cloud service for real-time big data analysis Google BigQuery. A year later, it was integrated into the paid version of Google Analytics Premium. An updated version of BigQuery is able to analyze up to 100,000 rows of data per second. Google has recently introduced a new specialized Cloud Bigtable database, which is suitable for big data better than its predecessor Cloud Dataflow.
In Russia, Google's big data solutions can be purchased from authorized resellers - the Russian branch of the Ukrainian company OWOX and such local agencies as iConText, Adventum, “Kokos”, AdLabs and i-Media According to the open sources, BigQuery service is used by M.Video, Ulmart, Svyaznoy, Ozon.Travel, Eldorado, Onlinetours, Anywayanyday and VimpelCom.
The company was founded in 2006 as a cloud storage service. In recent years, AWS expanded the big data solutions lineup. It consists of Amazon DynamoDB NoSQL data-base, RDBMS Amazon RDS, real time streaming data analysis service Amazon Kinesis, petabyte data store Amazon Redshift, online file storage service Amazon Glacier. AWS also provides Hadoop via Amazon Elastic MapReduce cloud service.
As part of a special support program AWS gives young entrepreneurs a free access to their cloud resources. Because of that the company's services are used by many Russian and foreign startups. Skolkovo fund joined the AWS Activate program last year, providing its residents access to Amazon products. Among other AWS users there’s a large domestic industry website Banki.ru.
Dataminers extract the knowledge from big data accumulated by the customers. According to some estimates, a global data analysis market is growing annually by 40% per year and by 2016 will exceed $ 50 billion.
Some data services operate based on model big data as a service (BDaaS), allowing you to upload data to the cloud and get the result. They keep the entrepreneurs from hiring the expensive staff and building own infrastructure. And if the customer needs a functionality broader than standard - you can order an upgrade.
Datamining services are more accessible than expensive equipment for small and medium business. ‘Regardless of the specialization of the customer, ready to analyze data service allows to quickly gain a competitive advantage and adapt to changing market conditions,” - big data architect at AT Consulting Alexey Bednov wrote in his column.
The majority of Yandex products are based on the analysis of big data arrays – the search engine, machine translation, spam filter, ad targeting, recommendations, speech and image recognition, prediction of traffic jams. The IT-company started to use their own technologies for external customers from 2012. Since then, the domestic IT-giant has done projects for oil companies (Rosneft and the Norwegian Statoil), predicted the customer attrition for the unnamed telecom operator, searched the efficient aircraft, and reduced the failure rate of the European ATMs.
In December, the IT-company announced the creation of Yandex Data Factory International Division. It specializes in processing large amounts of data for large businesses. Yandex Data Factory’s main clients are telecom, banks, retail and industrial facilities. YDF has developed a system that forecasts the traffic jams and accidents for Rosavtodor; it predicts player attrition for the online game developer Wargaming, and it is working with the British biopharmaceutical company AstraZeneca in the field of public health. In July YDF became Sberbank’s big data consultant. In August the company signed an agreement with Magnitogorsk Metallurgical Plant to establish a project to optimize the steel melting. Yandex uses its own solutions for big data analysis.
The company has been developing the datamining algorithms for solving business tasks since 2012. Its analytic solutions are addressed to retail, banks, transport, telecom, health care, insurance and the state. Algomost consults, creates the algorithms and supports their further development. The client only sets the task - for example, to increase the profits, to reduce the costs, to optimize the business processes, to surpass the competition, to attract new customers and partners, etc. Algorithms are developed not only by Algomost’s own developers but also by independent dataminers, whom the company finds through the open competitions (more than a thousand professionals worldwide). In 2013, the Algomost became a resident of Skolkovo IT-cluster.
Russian IT-holding company entered big data market in 2004, when it began to develop an analytical platform for media field monitoring service “Medialogia”. IBS developed the algorithms for the extended scoring, enriching customer profile, anti-fraud; it also analyzed the transactions for the clients in the financial sector. For government agencies the company solved the text analytics tasks, and helped to build big data infrastructure. IBS worked in cooperation with Yandex Data Factory on the traffic situation prediction system for Rosavtodor.
IBS has a portfolio of big data handling solutions for telecom operators, banks, retail and the public sector. It consults a wide range of clients on the data governance - corporate data management strategy as a source of efficiency. The company is working with key suppliers of the big data solutions: SAP, Oracle, IBM, SAS, Teradata, etc.
Perm-based BI-system developer is the Russian custom software market leader and sells its products in more than 70 countries. Prognoz’s flagship software development Platform includes a range of tools from classical to advanced BI analytics and data discovery capabilities. Last October the company released an updated version of the platform, extending its ability to work with big data. It is integrated with the hardware and software of Oracle Exadata, IBM Netezza and EMC Greenplum, supports the distributed storage and processing of big data in the Hadoop Hive, HiveQL and cloud operating.
Prognoz has specialized analytical solutions for the public sector, corporations, financial and other industries. Prognoz Platform is used by Russian state agencies, banks, research organizations and large companies - more than 200 implementations in the country.
Russian IT-company has implemented the big data projects since 2012. There are banks, telecom operators and government among the company’s clients. AT Consulting searched the opportunities to improve Moscow transport system, created antispam bots, analyzed customer attrition, etc. One of the biggest clients of the company is VimpelCom, the industrial cluster of big data was created for the company. For example, targeted customer offers, based on their location data, statistics, consumption of services, as well as a variety of network data, are made using the cluster online.
The company provides services based on big data technologies and solves customers’ tasks individually. Data-Centric Alliance ready-made solutions are used in the digital marketing. The product line-up consists of the programmatic platform Exebid DCA, big data management platform Facetz.DCA, platform for the sale of advertising inventory Spicy, recommendations service for Booster website, client portrait calculation Prizma client, a tool for attracting Internet audience SmartTDS.
The company develops individual projects for some telecom operators, banks and retailers. In July Data-Centric Alliance together along with Moscow Subway Wi-Fi provider Maxim Telecom launched the advertising platform for small and medium-sized businesses. In early August, the company made the outline of 30 leading online media audience using big data.
CleverData is the Lanit group of companies’ subsidiary (established in 2014). It introduces their partner and solutions for processing large data. CleverData analyzes the customer's client base; the company constructs the internal data management platform that optimizes the processes of RTB-advertising and builds operational performance management system based on Splunk. Target marketing is provided by data management platform 1DMP and monetization and data enrichment platform Data Marketing Cloud. The consulting company is working with IBM, Oracle, Teradata, Splunk, Aerospike and Sloudera. Last October CleverData announced the creation of a universal data exchange that will enable providers and consumers to agree on the big data sharing conditions.
Big data laboratory builds highly loaded big data warehouses and business analytics systems. EasyData is known for bringing HP Vertica solutions to Russia. In 2013, they implemented the system of database management in Otkrytie bank, and before that - in Yota Networks.
In 2008, IT-consulting became the main activity of the company. Among other services, it develops the big data processing and storage processes for their customers. Glowbyte Consulting implemented big data technologies in Tin’koff bank, Uralsib bank, OTP Bank, Leto Bank, BCS Financial Group and telecom operator Dom.ru. Integrator is a partner of the leading vendors - SAP, Oracle, EBM and others.
The startup offers big data solutions for financial institutions. By analyzing big data from the Internet they help banks to attract new customers, to communicate with the non-cooperative debtors, to verify the identity of the potential borrower, to assess creditworthiness and to detect fraud.
In 2014 the company became the Skolkovo IT cluster resident. In March 2015, Double Data attracted 200 million rubles in investments for new geographic and industry markets expansion from LETA Capital and SimileVenturePartners. In particular, the company sees potential in solving telecom, insurers, tour operators and e-commerce tasks. On their website they say they are ready to develop new products for the customers’ tasks.
St. Petersburg-based company is engaged in the commercial development, research and free training data science specialists. DataMining Labs helps to increase the marketing, finance, HR and manufacturing efficiency by processing the collected by the customer data. For example, the company analyzed the financial transactions traffic, detected the log-file anomalies of the web-services, predicted user backtrack.
The project provides training for the local big data industry, forms a community of data science experts, it helps the employers to look for data scientists and executes large dataminig orders for the public sector. For example, now MLClass applies machine learning techniques (hierarchical clustering and text mining) for estimating the efficiency of domestic business development institutions commissioned by the analytical center of the Russian Government.
The Ryazan company has focused on the development of data analysis software since 1999. As a result, long-term developments have resulted in BaseGroup Labs flagship product - BI-platform Deductor. It is based on ready-made solutions for scoring, maintaining the quality of customer data, procurement planning. BaseGroup Labs introduces big data analysis systems, provides technical support, educates professionals and acts as the vendor of Deductor platform.
For example, the company built the methodology to identify anomalies for “Obschestvennoe mnenie” Foundation, loan approval system for MTS Bank, the epidemics spread predictive model for Anti-Plague Research Institute “Microbe”.
The company opened a data analysis laboratory in 2011. Global Innovation Labs implements its algorithms on large retailers’ data. The service analyzes cheques, traffic organization categories, the effectiveness of marketing campaigns, customer behavior in store, their loyalty, and other metrics. Identified patterns help to optimize marketing, products assortment and pricing. Global Innovation Labs does not name their clients.
The company entered the big data market in 2010. Their main product is IQPlatform analytical platform. It works with both structured information, and with the raw data from disparate sources. IQPlatform solves the task of clients and partners infromation enrichment and supports the sales and optimizes the marketing, technological and competitive intelligence, improves the quality of customer service, security and risk management. IQ Men Business Intelligence developed projects for Sberbank, Vnesheconombank, the Russian Space Agency, Rostelecom, Russian Helicopters and FGC UES. The company’s partners are Oracle and IBM.
System integrators implement big data analysis system on the client side. They act as intermediaries between the technology and business. This is an option for those who are not satisfied with ready-made solutions and cloud computing. “The advantage of an integrator is that it can combine the products from different vendors that complement each other”, - IBS technology director Sergei Kuznetsov said in Computeworld interview.
The company began working with big data in 2013. They develop and deploy analytical systems for telecom, retail, banking, healthcare, government agencies and municipal services. In addition, the “Fors” offers ready-made software for the analysis of audiences using the data from social networks (ForSMedia) and the formation of contractor review. The company is an official distributor and a platinum partner of Oracle.
The integrator is closely associated with EMC, HP, Oracle and Microsoft, Intel – “Croc” competence center works with their solutions. The company started to implement big data projects in 2013. The “Croc” specialists built a model to reduce customer attrition for a major telecom operator, forecasted the passenger flow for the “Central Suburban Passenger Company”, and are now implementing a project in some major insurance companies. In 2014, the big data reached 1% of the “Croc” revenue.
Antispam, antifraud, programmatic-advertising and product recommendations are all built upon big data analysis technology. To use the ready-made services you do not need any additional server or consultants or data scientists. These systems take data from the open sources - social networks, websites, forums and media. This offers customers opportunities for digital marketing with no infrastructure costs.
Big data is a central figure in the RTB-advertising ecosystem. Data Management Platform (DMP) collects information about the users in the form of audience segments, data exchange - in the form of anonymised profiles. This data provide the most accurate targeting of RTB-advertising, while minimizing the costs for the advertiser and potential buyer’s irritation. Such services are offered by local companies Auditorius, Data-Centric Alliance, RTB Media, RuTarget / Segmento, Between Digital, Hubrus DSP, Adfox, AdRiver, GetIntent, Kavanga and others.
Big data from the open sources are operated numerous trade recommendations services (Retail Rocket, Crosss, REES46, “1C-Bitrix Big Data”), content personalization (Flocktory, Usalytics) and targeted marketing (Opiner, SmartBox eCRM, Witget). On this basis, they are also part of the Russian market of large data.
The oldest domestic IT-companies analyze big data in-house. They improve their own services, target advertising and personalize content.
The holding vengeance had used big data technologies long before the term big data emerged. The first such project was a web analytics system “Rating Mail.Ru”. Now the big data analysis is integrated in almost all the products of the company – “Target.Mail.Ru”, “Mail.Ru Mail”, “Odnoklassniki”, “Moy Mir”, “Mail.Ru search” and others. With the help of big data Mail.Ru filters spam, targets ads, optimizes the search, accelerates technical support, analyzes the behavior of users, offers them contacts and subscriptions. For offline data processing company uses Hadoop platform, for online - own development NoSQL DBMS Tarantool.
The media holding initially used big data in their search engine. Last couple of years, the company activated the datamining division. Rambler use big data technologies for ad targeting, content personalization, spam and bot blocking, natural language processing. The company uses the following big data platforms: Hadoop/Spark /Mahout and Python Scipy/Scikit-learn. Rambler is planning to master advertising technologies and content personalization in the future.
Also, Rambler puts on the development of content analytics services for PR. In July, it acquired 51% of stake share of RCO, which produces applications for intellectual processing of texts in different languages. The RCO products are used by Gazprom, the Ministry of Justice, Central Bank, Federal Security Service, Rosnano, MegaFon, Sberbank and others.
And now it is time to take a closer look at the examples of successful implementation of data processing technology. The telecom-operators are more active there: after mastering the datamining, they not only improved the quality of their services, but also turned the collected data into the liquid assets in high demand among bankers and officials.
The operator began to master big data processing technology two years ago. The main objective of the company is the optimization of costs and customer service improvement. Last year, Megafon agreed with Moscow government to provide information about the structure of the capital's population.
In 2013, Megafon became interested in geoanalytics - initially for network load forecast. Today it became a separate service for the passenger traffic analysis of the transport companies. The app shows the volume of passenger traffic, popular routes and mode of transport layout. In July, the operator started negotiations with the Russian Railways, offering it their solutions to predict the popular routes. The joint project will start no earlier than 2016.
In the meantime, big data brings around 1% of Megafon’s revenue. The telecom operator uses the solutions based on Hadoop platform to work with big data arrays. The company’s priority is customer information confidetiality, that’s why it doesn’t third party developments for the analysis.
Telecommunication holding VimpelCom uses big data analysis for monitoring the customer service quality, service and plan selection, antifraud and antispam, call center optimization by predicting causes of the call and other tasks. A special division of the company is responsible for the development and implementation of big data solutions. The data sets are analyzed using Hadoop, IBM SPSS, Apache Spark and Vowpal Wabbit.
Last May VimpelCom presented the pilot project “Smart Alert”. The technology warns people in the emergency area, as well as those who can get there.
At the end of May 2015 the operator launched a pilot project to estimate the credit solvency of its customers. About 20 banks joined the experiment. They get impersonal scoring points from VimpelCom, calculated on payments for mobile communication, service payment using mobile account and even geolocation data.
The company cooperated with the Genplan Institute of Moscow, St. Petersburg Transport Department, and recently won Moscow Department of Information Technologies tender for SMS-information of the Moscovites (the contract is worth 78 million rubles).
The company has implemented big data solutions since 2011. Information on the Internet traffic usage, the types of devices used, the communication circle and subscriber purchases allows MTS to make personalized offers for customers. The statistics of subscribers’ movements is used to predict the network load forecasting. The mobile operator provides the same data to the Government of Moscow within the joint project for the development of urban infrastructure. As expected, mobile geoanalytics will help the authorities to determine the location of new highways and subway stations. MTS along with banks were involved in the pilot subscriber scoring project. The product will be ready before the end of the year, after the completion of the technical solutions for the evaluation of the borrower's risk.
Also with the help of big data the company intends to predict the behavior of subscribers and fight against the fraud, to develop ad targeting, to improve the quality of network coverage, enhance the management efficiency of its own retail network and develop radio network based on the subscriber data. The operator is using Apache Hadoop, Apache Spark, Cloudera Impala, Teradata database and SAS solutions for big data storage and processing.
The bank's strategy for 2014-2018 marks the importance of big data analysis for the quality customer service, risk management and cost optimization. Now the bank is using big data for risk management, anti-fraud, segmentation and credit solvency estimation of the customers, staff management, queue forecasting in the bank branches, employees’ bonus calculation and other tasks.
According to CNews, Sberbank uses Teradata, Cloudera Hadoop, Impala, Zettaset, a stack of Apache products (Hadoop, HBase, Hive, Mahout, Oozie, Zookeeper, Flume, Solr, Spark, etc.), specialized databases (Neo4j, MongoDB, etc. .d.), and its own datamining solutions, predictive / prescriptive-analytics, natural language processing.
The organization has its own big data lab. The bank intends to integrate more internal data types and use external sources (e.g. data from the social networks). In March, Sberbank acquired the advertising platform Segmento, to use its data to personalize its offerings and attract new customers. In July, the bank hired Yandex as a consultant for big data analysis.
The bank uses big data customer attrition segmentation and management, financial reporting, social network and forum comments analysis. It uses Teradata solutions, SAS Visual Analytics and SAS Marketing Optimizer.
Alfa-Bank started using big data in 2013. It uses these technologies for the social networks analysis and website users’ behavior analysis, credit rating, customer attrition prediction, content personalization and secondary sales. The company works with Oracle Exadata storage and processing platform, Oracle Big Data Appliance and Hadoop framework.
Alfa-Bank views the recommendation systems, the product lineup analysis and predictive customer behavior analysis as the additional monetization possibilities.
The bank manages risks, analyzes the needs of potential and existing customers using EMC Greenplum, SAS Visual Analytics and Hadoop. Big data is also involved in the scoring, marketing and sales.
The bank uses big data for scoring, antifraud, prompt reporting, offer personalization, prescoring reputation check of the potential borrowers, providing information to the regulators and other tasks.